Future wireless networks are anticipated to evolve by aerial communication platforms. Nonetheless, the operational lifespan and efficacy of transceivers such as unmanned aerial vehicle (UAVs) and Internet of Things (IoT) devices are strictly prohibited by their constrained onboard power sources. This paper focuses on an aerial network configuration where a UAV harvests solar power to serve energy-limited IoT devices through simultaneous wireless information and power transfer. In this setup, the UAV and the IoT devices, each are equipped with energy and data buffers. This system also benefits from rate splitting multiple access for efficient interference management. Upon optimizing the system efficacy, we formulate a long-term resource allocation problem to maximize the time-averaged energy efficiency. To address this stochastic and non-convex optimization problem, we propose a multi-stage solution strategy. Firstly, by leveraging Lyapunov optimization theory, we transform the long-term stochastic problem into an equivalent deterministic short-term form. Next, by recasting this equivalent problem into Markov decision process, we propose a resource allocation mechanism based on actor-critic hindsight experience replay (AC-HER), tailored to capture the problem dynamics and optimize its variables. Moreover, given the UAV high mobility and the system reconfigurations, we fortify the trained AC-HER model with meta-learning strategy, enhancing its adaptability to system variations. Simulations verified that the proposed resource allocation strategy considerably outperforms its counterparts.

The expansion of Internet of Vehicles (IoV) technology brings significant cybersecurity and privacy concerns. This research study addresses cybersecurity challenges within the IoV and Intelligent Transportation System (ITS). It explores machine learning applications for detecting and preventing cyberattacks on the IoV network and autonomous vehicles, with the goal of developing and evaluating algorithms tailored to enhance IoV security, intrusion detection, and privacy. In this paper, we adopted a clustered machine learning model using Federated Learning and Convolutional Neural Networks (CNN) for IoV intrusion detection. Different scenarios involving centralized and decentralized clustering schemes are introduced. The proposed federated learning intrusion detection model has achieved a testing accuracy of 97.54 %, precision of 97.01 %, recall of 98.12 %, and an F1-score of 0.976.

Jamming attacks are among the most critical security threats to Wireless Sensor Networks (WSNs), as they can severely disrupt normal network operations, leading to data loss, network downtime, and reduced system performance. Intrusion Detection Systems (IDSs) have therefore become essential to protect WSNs. However, conventional IDSs often struggle to detect zero-day attacks, creating a significant security gap. To address this, Artificial Intelligence (AI)-based IDSs have been introduced, offering improved detection capabilities but frequently encountering high bias or variance issues, which reduce their reliability. Recently, ensemble learning (EL) has emerged as a promising approach to build more adaptable and data-resilient models by combining multiple learning algorithms. In this context, we propose AdaptiveBoost, an SDN-based Adaptive Ensemble Learning Framework, specifically designed for effective jamming attack detection in WSNs. The SDN integration allows AdaptiveBoost to optimize network traffic flow, identify anomalies in real-time, and adaptively fine-tune detection mechanisms based on current network conditions. We conduct several experiments to evaluate AdaptiveBoost using real-world WSN attacks; using the well-known public network security dataset, WSN-DS, show that AdaptiveBoost outperforms AI-based algorithms in terms of accuracy, precision, recall, and F1 score, while achieving a remarkable reduction in training time by a factor of 235, making it an efficient, scalable solution for securing WSNs against jamming attacks.

Advancements in autonomous vehicle technology depend on the development of object detection systems that efficiently balance speed and accuracy. This study evaluates real-time object detection models, with an emphasis on all YOLO kinds from v1 to v10. It draws attention to significant enhancements in accuracy and speed, remarkably with YOLOv9 and YOLOv10, which triumph a high Mean Average Precision (mAP) of 0.98, surpassing earlier YOLO versions and opposing algorithms. We reveal that YOLOv10 stands out for its finest trade-off between accuracy and computational efficiency, making it a powerful nominee for autonomous vehicle applications. The paper highlights the worth of picking the suitable model based on the specific requirements of the vehicle system. By utilizing extensive datasets such as Berkeley DeepDrive 100K and VisDrone, we prove that YOLOv10 can detect crucial road objects, including vehicles, traffic signs, and pedestrians, training the model for real-world deployment.

Unmanned Aerial Vehicles (UAVs) have become essential for various applications, including surveillance, logistics, and disaster response. However, their limited battery capacity and frequent need for recharging disrupt mission efficiency, especially in critical operations. Dynamic Wireless Charging (DWC), which provides in-flight charging autonomously, offers a promising solution to extend operational time. Deep Reinforcement Learning (DRL) enhances this approach by optimizing energy management, charging strategies, and trajectory planning based on real-time conditions. This paper explores the integration of DRL, DWC, and emerging technologies like 6G communications and IoT, aiming to improve UAV energy efficiency and mission reliability. It reviews current research on DRL for UAV charging and trajectory planning, discusses limitations in existing studies, and proposes future research directions, including the integration of laser beaming and hybrid DRL models. The goal is to create more autonomous, sustainable, and efficient UAV systems for diverse applications in intelligent transportation systems (ITS).

Real-time task processing is a critical challenge in vehicular networks, where achieving low latency and minimizing dropped task ratio depend on efficient task execution. Our primary objective is to maximize the number of completed tasks while minimizing overall latency, with a particular focus on reducing number of dropped tasks. To this end, we investigate both static and dynamic versions of an optimization algorithm. The static version assumes full task availability, while the dynamic version manages tasks as they arrive. We also distinguish between online and offline cases: the online version incorporates execution time into the offloading decision process, whereas the offline version excludes it, serving as a theoretical benchmark for optimal performance. We evaluate our proposed Online Dynamic Cost-Driven Algorithm (On-Dyn-CDA) against these baselines. Notably, the static Particle Swarm Optimization (PSO) baseline assumes all tasks are transferred to the RSU and processed by the MEC, and its offline version disregards execution time, making it infeasible for real-time applications despite its optimal performance in theory. Our novel On-Dyn-CDA completes execution in just 0.05 seconds under the most complex scenario, compared to 1330.05 seconds required by Dynamic PSO. It also outperforms Dynamic PSO by 3.42% in task loss and achieves a 29.22% reduction in average latency in complex scenarios. Furthermore, it requires neither a dataset nor a training phase, and its low computational complexity ensures efficiency and scalability in dynamic environments.

An overview of the dynamic wireless charging (DWC) system design and architectures is presented to highlight its profound impact within the dynamic framework of 6G-enabled intelligent transportation systems (ITS). A historical overview of DWC architecture is provided to trace its evolution and highlight emerging trends. Thus, establishing a foundational understanding of this rapidly developing field. This paper also focuses on the management of charging requirements for both connected and autonomous electric vehicles (CAEVs) and unmanned aerial vehicles (UAVs). A survey of innovative charging reservation strategies that are vital for optimal use of DWC infrastructure is presented. Further, the effect of early and late-arriving vehicles on DWC reservation systems is explored to highlight areas of improvement for research. Finally, we propose our meticulously designed architecture for the DWC reservation and trip planning for efficient charging of both CAEVs and UAVs. This is concluded by the presentation of innovative strategies to manage early and late arrival scenarios of both CAEVs and UAVs. Thus, promoting a more sustainable, efficient, and interconnected future of CAEV and UAV charging within the 5G/6G ITS.

This paper introduces a novel LSTM GAN model for trajectory prediction in Connected and Autonomous Vehicles (CAVs), combining LSTM’s time-series data handling with GAN’s data generation capabilities. Designed to accurately adapt to various driving scenarios, the model’s efficacy is evaluated in both short and long-trajectory prediction contexts. Initial results show that incorporating dynamic features like velocity and acceleration significantly enhances short-term trajectory predictions. However, long-term predictions pose challenges, particularly in accurately determining the final position. Addressing these issues, the paper suggests model refinements and training adjustments, alongside alternative evaluation metrics. This approach aims to improve the model’s stability and accuracy, especially in complex scenarios. The LSTM GAN model emerges as a promising tool for advancing trajectory prediction in autonomous vehicles, offering valuable insights for integrating LSTM and GAN in this field.

In the 6G era, addressing charging challenges for electric vehicles is paramount. This paper focuses on mitigating concerns for both Connected Autonomous Electric Vehicles (CAEVs) and Unmanned Aerial Vehicles (UAVs). CAEV users face range anxiety, while UAV operators contend with limited battery sizes. The paper introduces a dynamic wireless charging (DWC) reservation and trip planning system, powered by 6G, vital for future smart cities. It provides a literature review on CAEV and UAV charge scheduling, proposing a novel system design tailored for 6G-enabled Intelligent Transportation Systems (ITS), where UAVs serve CAEVs. Notably, for vehicle-to-vehicle DWC and communication, laser technology is utilized, ensuring reliability and efficiency. A dynamic arrival handling protocol addresses unpredictable vehicle arrivals. Simulation results showcase the system’s efficiency, optimizing charging and reducing wait times. With the impending 6G era, the paper aims to advance charging infrastructure for intelligent, flexible, and harmonized electric vehicle charging operations.

Incorporating machine learning algorithms with Intrusion Detection System (IDS) can detect network intrusions without human intervention and aims for Zero Touch Networks (ZTN). In this research, an automatic network-based features and host-based features integrated intrusion detection scheme is presented to improve the performance of network attack detection under the SCVIC-CIDS-2021 dataset which is derived from the integration of network packets and host logs of the CSE-CIC-IDS2018 dataset. Auto-encoder (AE) and Gated Recurrent Unit (GRU) are utilized for feature derivation to overcome the dimensionality mismatch between network-based and host-based features. The knowledge-based Prior Knowledge Input (PKI) model is used to combine unsupervised extra knowledge with a pre-trained supervised model for the final classification results. The results of the experiment reveal that the integration of network-based and host-based features is effective and the PKI model improves the performance of the original ML classification algorithm as well. Under the test set, the maximum achievable macro average F1-score reaches up to 97.08% which points out approximately 9% improvement compared to the best baseline performance.

Multi-task learning (MTL) is a rapidly growing field in the world of autonomous vehicles, particularly in the area of computer vision. Autonomous vehicles are heavily reliant on computer vision technology for tasks such as object detection, object segmentation, and object tracking. The complexity of sensor data and the multiple tasks involved in autonomous driving can make it challenging to design effective systems. MTL addresses these challenges by training a single model to perform multiple tasks simultaneously, utilizing shared representations to learn common concepts between a group of related tasks, and improving data efficiency. In this paper, we propose a scalable MTL system for object detection that can be used to construct any MTL network with different scales and shapes. The proposed system is an extension of the Mask R-CNN. It is designed to overcome the limitations of learning multiple objects in multi-label learning. We have a typical network and evaluated its performance on the Berkeley Deep Drive 100KBDD100k dataset. The experimental results demonstrate that the proposed MTL network outperforms a base single-task network, Mask RCNN, in terms of mean average precision at 50 (mAP50). Furthermore, we have also conducted a comparison with the existing representative approaches.

To address the challenges posed by road weather management, there is a growing need for a comprehensive system that can collect, analyze, and disseminate real-time road weather information to connected and autonomous vehicles. Such a system must be able to assess the impact of weather conditions quickly and accurately on-road operations and provide relevant information to road users in real time. Edge cloud technology provides a solution to the challenges of road weather management by enabling real-time data collection, analysis, and dissemination. The purpose of this paper is to propose a comprehensive edge cloud-enabled road weather management system for connected and autonomous vehicles. The proposed system incorporates the use of Message Queuing Telemetry Transport (MQTT), a two-stage Fuzzy Inference System (FIS), and zone-based alerting. We have evaluated the performance of the proposed system through simulation experiments.

Through the digitization of essential functional processes, Industry 4.0 aims to build knowledgeable, networked, and stable value chains. Network trustworthiness is a critical component of network security that is built on positive interactions, guarantees, transparency, and accountability. Blockchain technology has drawn the attention of researchers in various fields of data science as a safe and low-cost platform to track a large number of eventual transactions. Such a technique is adaptable to the renewable energy-trade sector, which suffers from security and trustworthy issues. Having a decentralized energy infrastructure, that is supported by blockchain and artificial intelligence, enables smart and secure microgrid energy trading. The new age of industrial production will be highly versatile in terms of production volume and customization. As such a robust collaboration solution between consumers, businesses, and suppliers must be both secure and sustainable. In this article, we introduce a cooperative and distributed framework that relies on computing, communication, and intelligence capabilities of edge and end devices to enable secure energy trading, remote monitoring, and network trustworthiness. The blockchain and federated learning-enabled solution provide secure energy trading between different critical entities. Such a technique, coupled with 5G and beyond networks, would enable mass surveillance, monitoring, and analysis to occur at the edge. Performance evaluations are conducted to test the effectiveness of the proposed solution in terms of reliability and responsiveness in a vehicular network energy-trade scenario.

Due to the absence of distinct boundaries, wireless networks are vulnerable to a variety of intrusions. As the number of intruders has increased, the risks on critical infrastructures monitored by networked systems have also increased. Protecting shared information using effective and robust Intrusion Detection Systems (IDSs) remains a critical issue, especially with the growing implementation of vehicular networks. Building an IDS that detects threats efficiently with maximum accuracy and detection is a challenging undertaking. Machine Learning (ML) mechanisms have been successfully adopted in IDSs to detect a variety of network intruders. Split learning is considered one of the main developments in creating efficient ML approaches. In utilizing the Split Learning approach, an IDS is successful in performing at higher accuracy, and detection rate as well as a higher classification performance (Precision, Recall). In this work, a Split Learning-based IDS ($SplitLearn$) for Intelligent Transportation System (ITS) infrastructures has been proposed to address the potential security concerns. The proposed model has been evaluated and compared against other models (i.e., Federated Learning ($FedLearn$) and Transfer Learning ($TransLearn$)-based solutions). With the highest accuracy and detection rates, the proposed model ($SplitLearn$) outperforms$FedLearn$and$TransLearn$by 2 to 5 % respectively. We also see a decrease in power consumption when utilizing$SplitLearn$versus$FedLearn$.

Autonomous driving is strongly contingent on perception and motion prediction for scene understanding. In this paper, we propose LIDAR Network (LidNet) to boost perception and motion prediction accuracy by redesigning MotionNet architecture. MotionNet is a new real-time encoder-decoder model that achieves joint perception and motion prediction at a pixel level. LidNet improves MotionNet performance by replacing every two spatial convolution layers in its encoder-decoder architecture with residual blocks and relies on average pooling rather than strided convolution for spatial reduction. In addition, we adjust the lateral skip connections linking encoders and decoders to result in a symmetric network. The global temporal maximum pooling layers on the lateral connections are replaced with temporal average pooling. Further, we introduce a center layer between the encoder-decoder architecture, with no spatial reduction applied at the lowest levels. Our extensive evaluation performed on the nuScenes dataset confirms that LidNet outperforms the state-of-the-art and operates in real-time.

The number of Internet of Things (IoT) devices being deployed into networks is growing at a phenomenal pace, which makes IoT networks more vulnerable in the wireless medium. Advanced Persistent Threat (APT) is malicious to most of the network facilities and the available attack data for training the machine learning-based Intrusion Detection System (IDS) is limited when compared to the normal traffic. Therefore, it is quite challenging to enhance the detection performance in order to mitigate the influence of APT. Therefore, Prior Knowledge Input (PKI) models are proposed and tested using the SCVIC-APT-2021 dataset. To obtain prior knowledge, the proposed PKI model pre-classifies the original dataset with unsupervised clustering method. Then, the obtained prior knowledge is incorporated into the supervised model to decrease training complexity and assist the supervised model in determining the optimal mapping between the raw data and true labels. The experimental findings indicate that the PKI model outperforms the supervised baseline, with the best macro average F1-score of 81.37%, which is 10.47% higher than the baseline.

The advancements of Edge and Internet of Things (IoT) devices in terms of their processing, storage and communication capabilities, in addition to the advancements in wireless communication and networking technologies, have led to the rise in Intelligent Edge-enabled IoT architectures. Federated Learning (FL) is one example in which intelligence is adapted to the edge to offload some of the processing load from centralized entities and maintain secure localized model training. With Health 4.0, it is anticipated that distributed and edge-supported Artificial Intelligence (AI) will enable faster and more accurate early-stage disease discovery that relies significantly on intelligent remote and on-site IoT devices. Given that healthcare systems are highly scrutinized by both governments and patients to maintain high levels of data privacy and security, FL coupled with the support of blockchain will provide an optimal solution to reinforce today's healthcare frameworks. In this paper, we propose a FL-enabled framework for healthcare systems that is supported by edge-computing, blockchain and intelligent IoT devices. The solution considers a pneumonia detection use-case as a proof-of-concept and is applicable to an extended set of health-related use-cases. Different pre-trained models are compared against the proposed FL-supported model, namely, CNN, GG16, VGG19, InceptionV3, ResNet, DenseNet, and Xception. Results show high model accuracy attainment and significant improvements in terms of data privacy.

Connected and Autonomous Vehicles (CAVs) are vehicles that detect and communicate with the surrounding vehicles and infrastructure automatically to perform functions such as traffic sign detection, object tracking including vehicles and pedestrians, etc. CAVs offer accurate distance sensing for shorter headway as well as provide reduced reaction time, and ultimately increase the roadway capacity and efficiency. These promising benefits of CAVs can realize through their platooning. CAV platooning is becoming appealing due to the benefits on improved traffic efficiency, reduced fuel consumption and emissions. However, these benefits may not be totally realized in the mixed traffic scenario. For instance, cut-in or cut-through maneuvers by the non-platooning vehicles may be the major obstacle to maintaining platoon integrity. In this paper, not only the implementation of CAV platooning is demonstrated using CARLA but also the impact of the non-platooning vehicles in the CAV platooning in different scenarios is investigated. For this purpose, the non-platooning vehicles have been categorized into priority and non-priority vehicles. Results show how the platooning vehicles are affected by the cut-through vehicles.

Connected and Autonomous Vehicles (CAVs) are vehicles that provide connectivity between other vehicles (V2V), infrastructure (V2I) and any things (V2X) using various communication technologies. Deploying CA V s can make transportation safer, improve mobility and provide benefits to the Smart city environment. For autonomous driving, lane detection/segmentation is one of important tasks, and changing lanes is one of the crucial driving decisions. This paper exclusively investigates drivable space segmentation and state-of-the-art deep learning model for instance segmentation. The results show that the selected Mask R-CNN model accurately detects and segments direct lane and alternative lanes with high confidence score.

Network trustworthiness is considered a very crucial element in network security and is developed through positive experiences, guarantees, clarity, and responsibility. Trustworthiness becomes even more compelling with the ever-expanding set of Internet of Things (IoT) smart city services and applications. Most of today’s network trustworthy solutions are considered inadequate, notably for critical applications where IoT devices may be exposed and easily compromised. In this article, we propose an adaptive framework that integrates both federated learning and blockchain to achieve both network trustworthiness and security. The solution is capable of dealing with individuals’ trust as a probability and estimates the end devices’ trust values belonging to different networks subject to achieving security criteria. We evaluate and verify the proposed model through simulation to showcase the effectiveness of the framework in terms of network lifetime, energy consumption, and trust using multiple factors. Results show that the proposed model maintains high accuracy and detection rates with values of$\approx 0.93$and$\approx 0.96$, respectively.

Next-generation vehicular networks will impose unprecedented computation demand due to the wide adoption of compute-intensive services with stringent latency requirements. Computational capacity of vehicular networks can be enhanced by integration of vehicular edge or fog computing; however, the growing popularity and massive adoption of novel services make edge resources insufficient. This challenge can be addressed by utilizing the onboard computation resources of neighboring vehicles that are not resource-constrained along with the edge computing resources. To fill the gaps, in this paper, we propose to solve the problem of task offloading by jointly considering the communication and computation resources in a mobile vehicular network. We formulate a non-linear problem to minimize the energy consumption subject to the network resources. Further-more, we consider a practical vehicular environment by taking into account the dynamics of mobile vehicular networks. The formulated problem is solved via a deep reinforcement learning (DRL) based approach. Finally, numerical evaluations are performed that demonstrates the effectiveness of our proposed scheme.

Wireless Networks lack clear boundaries which leads to security concerns and vulnerabilities to numerous kinds of intrusions. With the growth of cyber intruders, the risks on crucial applications monitored by networked systems have also grown. Effective and vigorous Intrusion Detection Systems (IDSs) for protecting shared information continues to be an essential task to keep private data safe especially in the healthcare sphere. Constructing an IDS that detects and returns information efficiently and with the highest accuracy is a challenging task. Machine Learning (ML) techniques have been effectively adopted in IDSs to detect network intruders. Reinforcement learning is considered as one of the main developments in ML. IDS mainly performs a higher accuracy rate, detection rate as well as a higher performance of a classification (ROC curve). According to these and to tackle the security issues, a Federated Reinforcement Learning-based Intrusion Detection System (FRL-IDS) in the Internet of Things (IoT) networks for healthcare infrastructures has been proposed. The proposed model has been evaluated and compared to a similar model (i.e. SVM system). The proposed model shows superiority over the SVM-steered IDS with accuracy and detection rates of ≈ 0.985 and ≈ 96.5%, respectively. This proposed infrastructure will not only aid in intrusion detection of large health care systems but also other wireless decentralized networks found across multiple real-world applications.

This paper proposes a profit maximization model for a Decentralized Electric Vehicle Supply Equipment (D-EVSE) equipped with a Photovoltaic system. We acknowledge a power connection to the central power grid when necessary. We design a Decentralized Profit Maximization Algorithm (DPMA) to help D-EVSEs take profits from the electricity price variation during the day when selling electricity to EVs or buying it from the grid. Finally, numerical simulations with MATLAB are conducted to prove the effectiveness of our proposed solution.

The field of self-driving vehicles (SDVs) is going viral among researchers from a broad spectrum of specialties. SDVs are expected to have profound impacts on the world once fully developed and deployed on roads. Hence, researchers are working assiduously together to accomplish this project. In this paper, we propose integrating motion prediction with sequential latent maximum entropy reinforcement learning, end-to-end, to train an agent to navigate autonomously in a simulated urban environment. The fusion of motion prediction for surrounding vehicles enhances traffic efficiency and safety. A novel network specialized in joint perception and motion prediction, named MotionNet, is selected in our paper to supply us with motion predictions. Our proposed system demonstrates that adding motion prediction enhances performance even further. Furthermore, our system relies merely on LIDAR sensor. CARLA simulator is used to conduct our experiments and extract outcomes.

A novel three-layer charging system design of static and dynamic wireless charging that can operate with the existing wired charging infrastructure and standards for Intelligent Transportation System (ITS) is presented. This internet of things (IoT) application is accompanied by a proposed handshake protocol that uses vehicle to infrastructure (V2I) and vehicle to grid (V2G) communications for fulfilling charging requests of connected and autonomous electric vehicles with the shortest possible route to the destination. The charging requests of the Electric Vehicle (EV) and Autonomous Electric Vehicle (AEV) users are fulfilled by dynamically distributing the request over the three different types of charging equipment, and the requests are serviced and billed for in a private and secure manner using two different proposed payment schemes with the encrypted virtual currency. The hardware independent system can detect misalignment of the connected vehicles on the wireless charging pads and the speed issue errors in dynamic wireless charging system as well as avoid free-riders. Finally, the presented system is simulated and is revealed to plan trips with minimum waiting times, travel costs and battery consumption per vehicle trip with efficiency of 90.25% charge delivery.

The adverse weather conditions and unforeseen road surface may negatively affect driving safety. To provide better roadway safety and mobility, Road Weather Information System (RWIS) have been implemented. The performance of the existing RWIS can be improved using various emerging technologies such as connected vehicle technologies and edge cloud computing. This paper presents development of a cost-effective and resource-efficient road weather management system using edge cloud and connected vehicle technologies, as well as deployment of fuzzy inference system as road weather hazard assessment means.

Perception and motion prediction are indispensable components to the smooth operation of autonomous vehicles and the safety of the surrounding environment. Strengthening the accuracy of perception and motion prediction in autonomous vehicles remains of paramount importance. Therefore, we propose an end-to-end multi-view fusion methodology applied to MotionNet backbone network to enhance the sharpness of both perception and motion prediction. MotionNet is a state-of-the-art real-time model designed for joint perception and motion prediction. Our multi-view input is based on a single LIDAR sensor and formed by the fusion of range view features with bird's eye view. We evaluate our proposed work on nuScenes dataset and demonstrate through experiments that our proposed extension to MotionNet using the multi-view fusion technique outperforms MotionNet in both perception and motion prediction, especially for small and distant objects.

Internet-based taxi service not only facilitates passenger travel but also effectively improves the utilization of transportation resources. Autonomous electric vehicle (AEV), as a future-oriented form of transportation, is more environmentally friendly and intelligent as it does not require a driver and uses green energy to fulfill the trip. Using idle AEVs for taxi service is an effective way to realize smart city transportation in the future. With the aim of supporting AEVs to provide taxi services, AEV Taxi Management and Dispatching Module (ATMDM), is proposed to support AEV management and scheduling in the AEV Taxi Service (ATS) system. By efficiently maintaining AEV status and information, ATMDM is able to realize the management of multiple AEVs as well as can also provide taxi service by matching orders with appropriate AEVs and providing route information based on the received trip requests. Compared with traditional taxi dispatching solutions, ATMDM fully considers the operational characteristics of AEV with better adaptability, which shows insight for the future means of transportation.

Volunteer computing uses Internet-connected devices (laptops, PCs, smart devices, etc.), in which their owners volunteer them as storage and computing power resources, has become an essential mechanism for resource management in numerous applications. The growth of the volume and variety of data traffic on the Internet leads to concerns on the robustness of cyberphysical systems especially for critical infrastructures. Therefore, the implementation of an efficient Intrusion Detection System for gathering such sensory data has gained vital importance. In this article, we present a comparative study of Artificial Intelligence (AI)-driven intrusion detection systems for wirelessly connected sensors that track crucial applications. Specifically, we present an in-depth analysis of the use of machine learning, deep learning and reinforcement learning solutions to recognise intrusive behavior in the collected traffic. We evaluate the proposed mechanisms by using KDD’99 as real attack dataset in our simulations. Results present the performance metrics for three different IDSs, namely the Adaptively Supervised and Clustered Hybrid IDS (ASCH-IDS), Restricted Boltzmann Machine-based Clustered IDS (RBC-IDS), and Q-learning based IDS (Q-IDS), to detect malicious behaviors. We also present the performance of different reinforcement learning techniques such as State-Action-Reward-State-Action Learning (SARSA) and the Temporal Difference learning (TD). Through simulations, we show that Q-IDS performs with detection rate while SARSA-IDS and TD-IDS perform at the order of .

The advances in today's IoT devices and machine learning methods have given rise to the concept of Federated Learning. Through such a technique, a plethora of network devices collaboratively train and update a mutual machine learning model while protecting their individual data-sets. Federated learning proves its effectiveness in tackling communication efficiency and privacy-safeguarding issues. Moreover, blockchain was introduced to solve many network issues in regard to data privacy and network single point of failure. In this article, we introduce a solution that integrates both federated learning and blockchain to ensure both data privacy and network security. We present a framework to decentralize the mutual machine learning models on end-devices. A blockchain-based consensus solution as a second line of privacy is used to ensure trustworthy shared training on the fog. The proposed model enables on-end device machine learning without any centralized training of the data nor coordination by utilizing a consensus method in the blockchain. We evaluate and verify our proposed model through simulation to showcase the effectiveness of the adapted scheme in terms of accuracy, energy consumption, and lifetime rate, along with throughput and latency metrics. The proposed model performs with an accuracy rate of ≈ 0.97.

In this paper, we address a decentralized management system based on noncooperative Game Theory (GT) for Electric Vehicles' (EVs') interplay with a Decentralized Electric Vehicle Supply Equipment (D-EVSE) located at the public supply station. Renewable energy production, such as photovoltaic energy (PV), is considered as the only power source for our D-EVSE. We propose a decentralized GT (D-GT) model aiming to optimize the EVs' interaction with the D-EVSE considering both EVs' satisfaction as well as the D-EVSEs' stability. Also, the D-GT model is used to choose the optimal available solution for EV charging or discharging processes that fulfill predefined constraints. Simulation results indicate that the proposed model can manage and control the interaction between EVs and D-EVSEs efficiently and effectively.

With the increase of cyber attack risks on critical infrastructures monitored by networked systems, robust Intrusion Detection Systems (IDSs) for protecting the information have become vital. Designing an IDS that performs with maximum accuracy with minimum false alarms is a challenging task. Ensemble method considered as one of the main developments in machine learning in the past decade, it finds an accurate classifier by combining many classifiers. In this paper, an ensemble classification procedure is proposed using Random Forest (RF), DensityBased Spatial Clustering of Applications with Noise (DBSCAN) and Restricted Boltzmann Machine (RBM) as base classifiers. RF, DBSCAN, and RBM techniques have been used for classification purposes. The ensemble model is introduced for achieving better results. Bayesian Combination Classification (BCC) has been adopted as a combination technique. Independent BCC (IBCC) and Dependent BCC (DBCC) have been tested for performance comparison. The model shows a promising result for all classes of attacks. DBCC performs over IBCC in terms of accuracy and detection rates. Through simulations under a wireless sensor network scenario, we have verified that DBCC-based IDS works with ≈ 100% detection and ≈ 1.0 accuracy rate in the existence of intrusive behavior in the tested Wireless Sensor Network (WSN).

With the recent surge in deploying aerial Optical Ground Wires (OPGW) as the infrastructure of optical networks, there is a challenging problem which is related to lightning strikes and their effect on the State-of-Polarization (SOP) experienced by dual-polarization coherent receivers. In network planning, all factors that concern the transporting traffic should be taken into consideration. When performing network planning, Routing and Spectrum Assignment (RSA) algorithms that use cost functions are invoked. We propose a cost function, for optical networks with OPGW links, that contains risk factor and meteorology information to reduce the impact of lightning strikes on live traffic.

In this work, we develop a dynamic multi-mode transportation model in which the passenger, for his trip, can use one or a combination of the transportation form such as the car, the bus and the bike. This model is based on the game theory concept based trip cost-optimization. The proposed system is implemented through a realistic scenario in a specific city using the OMNET++, VEINS, SUMO, MATLAB and the OpenStreetMap software tools. The results show that the average trip price and the average trip time are improved when using our proposed model.

Even though the electric vehicles (EVs) are getting greater attention in recent years, still a lot of advancement in EV technologies is required to support widespread adoption of EVs. A lot of attention is focused on the authentication and authorization mechanisms for the EV charging infrastructure. Existing EV charging networks extensively use RFID smart cards for authentication and authorization purposes. Furthermore, ISO/IEC (International Organization for Standardization/International Electrotechnical Commission) 15118 standard has defined certificate based authentication and authorization mechanism for EV charging. However, since these techniques are unimodal and single path, they have low security and can be vulnerable to various malicious attacks. Multimodal and Multi-pass Authentication mechanisms have been proposed for EV networks. Deploying such mechanisms, various attacks such as man-in-the-middle attacks, substitution attacks can be mitigated.

The demand for wireless services is becoming much more significant than the currently available spectrum could accommodate. Therefore, improvements at the physical layer alone cannot sustain such high data rates. Extreme densification of wireless networks (e.g., small cells) and the use of additional bandwidth are necessary to meet this increasing demand. On the other hand, multiple-input-multiple-output (MIMO) technology was also introduced to overcome the saturated data rate capabilities of conventional single antenna systems given the limited bandwidth and power levels. However, among various performance aspects and design problems regarding MIMO, precoding is one of the most crucial function components to ensure reliable communication. Without precoding, inter-stream interference can be severe even with cross-pol antenna design. However, the precoding could help to reduce the inter-stream interference and increase the signal strength along the desired signal subspace. In this work, a low complexity design a PHY-MAC precoder for sub-6 GHz backhaul small cell is proposed. The simulations were performed using an SUI-3 channel model for fixed wireless applications.

Summary Recent technology developments have produced small and smart biomedical sensors, which can be worn or implanted in the human body. These biosensors create closed wireless networks named Wireless Body Area Networks (WBAN). The WBAN will continuously observe the physiological state of patients for both diagnosis and prevention. Those include on‐body measurements such as the Electrocardiogram (ECG), Electroencephalogram (EEG), temperature, and blood pressure. Ultra‐Wide‐Band (UWB) is a technology that has received a lot of attention due to several unique features such as secure transmission, low noise, and low energy consumption. Given the fact that the patients' well‐being might be dependent on the accurate realization of such networks, a high level of design and implementation accuracy are maintained throughout the system. In this paper, we proposed an Impulse‐Radio Ultra‐Wideband system, which is composed of static biomedical nodes mounted on a patient's body to collect vital data and send it wirelessly to a central node or subsequent analysis by healthcare professionals. The performance of this network, such as the effect of node location, the number of transmitted symbols, multiuser interference, and intersymbol interference, is evaluated. We also study the physical layer and quality of service of this proposed architecture.

Electric vehicles (EVs) are likely to become very popular within the next few years. With possibly millions of such vehicles operating across the smart cities, smart grid energy providers can be directly impacted by the charging of EV batteries. In order to reduce this impact and optimize energy saving, in this article, we propose a coordinated model for scheduling the plug-in of EVs for charging and discharging energy. The model is based on a new decentralized Fog architecture for smart grid in order to reduce the completion and communication delay of EV energy demand scheduling. To enhance the scheduling of EV demands and predict the future energy flows, we propose a plug-in system of EVs based on calendar planning. We develop a mathematical formalism based on Markov chains using a multipriority queuing theory with cut-off discipline in order to reduce the waiting time to plug-in. We implement three planning algorithms in order to assign priority levels and then optimize the plug-in time into each EV public supply station. To the best of our knowledge, this is the first article that proposes a model that tries to save energy by planning the plug-in of EVs using a cut-off priority queuing model and a decentralized Fog architecture. We evaluate the performances of our solution via extensive simulations using a realistic energy loads from the city of Toronto, and we compare it with other recent works.

In this paper, we consider the Electric Vehicles (EVs) interaction with a decentralized energy storage system (DESS) located at the public supply station. To manage the EV charging and discharging process, we propose a scheduling algorithm aiming to maximize the EV drivers' satisfaction and minimize the DESSs' stress level. Simulation results using realistic scenarios are conducted to validate the proposed approach and demonstrate its efficiency and effectiveness while satisfying the defined constraints.

In order to secure smart metering infrastructure against false data injection attacks in smart grid, we propose in this paper a new hierarchical and distributed intrusion detection system (HD-IDS). The proposed HD-IDS is based on distributed Fog architecture using three hierarchical network levels (i.e., home area network, residential area network, and Fog operation center network). At each network level, we implement an IDS; thus, the system ensures three protection and detection levels. The problem is modeled using stochastic Markov chain process illustrating the transitions between different smart meter states. The advantage of the proposed HD-IDS solution is proved using extensive simulations over different performance metrics and compared with centralized architectures. The implementation is based on real-word traces of electricity consumption of the city of Toronto.

The Internet of Things (IoT) paradigm and its applications have been gaining popularity recently. The Intelligent Transportation System (ITS) is a major area of IoT applications. With ITS the transportation infrastructure is supported with advanced networking and computing technologies to better manage traffics on the roads. The Vehicular Ad-Hoc Network (VANET) stands out as an important technology under the ITS. The VANET technology supports different architectures for data communication, namely, vehicle-to-vehicle (V2V), vehicle-to-road-side (V2R), vehicle-to-infrastructure (V2I), and infrastructure-toinfrastructure (I2I). In V2R communication, data flow between vehicles and roadside units (RSUs) to convey important information about the road traffic and emergency situations. This data should be transferred with high probability of successful delivery. Also, the sensitivity of this data requires reducing the end-to-end communication delay. The IEEE 802.15.4 standard is one of the important candidate standards that supports the V2R communications. In this paper, we propose the Dynamic Window Algorithm (DWA); a backoff algorithm that targets improving the performance of V2R communications in terms of throughput and delay. This is attained by proposing changes to the operation of the standard Binary Exponent Backoff (BEB) algorithm (in IEEE 802.15.4 MAC). A Java-based simulation tool has been developed to simulate both BEB and DWA algorithms and conduct a comparison study between them. Our results show that in clusters of 20 nodes, the performance in terms of throughput and delay is improved by 32% and 88%, respectively, with DWA.

Wireless sensor and actuator networks are widely adopted in various applications such as critical infrastructure monitoring where sensory data in big volumes and velocity are prone to security vulnerabilities for the network and the monitored infrastructure. Despite the vulnerabilities of the big data phenomenon, intelligent data analytics technique can enable the analysis of huge amount of data and identification of intrusive behavior in real time. The main performance targets for any Intrusion Detection System (IDS) involve accuracy, detection, precision, F1 score and Receiver Operating Characteristics. Pursuant to these, this paper proposes a big data-driven IDS approach in Wireless Sensor Networks by harnessing reinforcement learning techniques on a hybrid IDS framework. We study the performance of RL-IDS and compare it to the previously proposed Adaptive Machine Learning-based IDS (AML-IDS) namely the Adaptively Supervised and Clustered Hybrid IDS (ASCH-IDS). The experimental results show that RL-IDS can achieve ≈ 100% success in detection, accuracy and precisionrecall rates whereas its predecessor ASCH-IDS performs with an accuracy level that is slightly above 99%.

In this paper, an affordable and suitable mobility system is developed for passenger with trip cost optimization in smart city concept. This system based on trip in the city by using multiple transportation forms of buses and carpooling. A Mobility Traffic Algorithm (MTA) is proposed to manage a passenger's specific needs based on real-time information of buses and carpooling. The proposed model is implemented with a realistic scenario in the city of Ottawa using the OpenStreetMap program and the OMNET++. The results show that passenger satisfaction is improved when using a combination of multiple transportation forms in the city. Also, the simulation is proved that the stress level of the buses and carpooling during the daytime is reduced to its minimum by using MTA model.

This paper presents a decentralized scheduling architecture for Electric Vehicles (EVs) energy management based on fog computing paradigm, where optimal load balancing algorithms are implemented using priority-queuing model. The proposed architecture consists of multiple decentralized fog operation centers that assist vehicle-to-grid (V2G) communication in order to manage and schedule EVs charging/discharging requests in real-time way and to maintain the electric smart grid stability. We introduce two scheduling algorithms; 1) priority levels assignment, 2) optimal load balancing of EVs requests over fog servers. The extensive simulations and comparisons with different scenarios proved that our proposed model reduces the response time and maximizes EVs utility. In addition, the proposed scheduling algorithms optimize the energy load during peak hours, and maintain the micro grid stability using real scenarios in the city of Toronto.

Wireless sensor networks have become integral components of the monitoring systems for critical infrastructures such as the power grid or residential microgrids. Therefore, implementation of robust Intrusion Detection Systems (IDS) at the sensory data aggregation stage has become of paramount importance. Key performance targets for IDS in these environments involve accuracy, precision, and the receiver operating characteristics which is a function of the sensitivity and the ratio of false alarms. Furthermore, the interplay between machine learning and networked systems has led to promising opportunities, particularly for the system level security of wireless sensor networks. Pursuant to these, in this paper, we propose Adaptively Supervised and Clustered Hybrid IDS (ASCH-IDS) for wirelessly connected sensor clusters that monitor critical infrastructures. The proposed ASCH-IDS mechanism is built on a hybrid IDS framework, and transforms the previous work by continuously monitoring the behavior of the receiver operating characteristics, and adaptively directing the incoming packets at a sensor cluster towards either misuse detection or anomaly detection module. We evaluate the proposed mechanism by introducing real attack data sets into simulations, and show that our proposal performs at 98.9% detection rate and approximately 99.80% overall accuracy to detect known and unknown malicious behavior in the sensor network.

A large-scale deployment of Electric Vehicles (EVs) not only provides mobility paradigm shift but also demands new requirements in the information and control components of the electric power grid. Some of barriers to the EV adoption could be lowered if Smart cities make available sufficient public EV Charging systems such that they facilitate EVs to be charged in those charging systems. In order to provide interoperability and reduce costly maintenance, open standards such as Open Charge Point Protocol (OCPP) are desired for communication in EV Charging systems. In this paper, we depict a smart management system for community-wide and public EV charging infrastructures in the Smart city known as SecCharge System as well as its implementation using OCPP.

In order to optimally schedule electric vehicles (EVs) energy charging and discharging demands, we propose in this paper a multi-level fog (MLF) model architecture. EVs energy demands in MLF are planned as charging and discharging calendars to handle with EVs energy demands in smart grid environment. Our work integrates a priority queuing model based on Markov chain analysis to schedule EVs energy calendars and allocate computing resources. Furthermore, we use the distributed feature of fog networks to cover micro grids. To this end, and to ensure the efficiency of resources allocation, we further propose two workload placement mechanisms for smart grid environment. Extensive simulations are performed under accurate assumptions and realistic environment based on real energy loads in the city of Toronto. The obtained results indicate the efficiency of the proposed MLF model in enhancing smart grid performance and saving EVs energy.

In coming years, attraction to alternative urban mobility paradigms such as Connected and Autonomous Electric Vehicles (CAEVs) will increase since CAEVs can significantly contribute to not only optimize traffic flow and improve road safety but also minimize dependence on fossil fuel and reduce carbon emission in urban areas. Nonetheless, there are several barriers towards widespread adoption of CAEVs. In order to have significant growth of CAEVs in urban areas, adequate number of charging facilities in urban areas is needed as well as an efficient smart CAEV charging management is required for managing and allocating charging station resources. In this paper, we have designed and implemented a system utilizing automated reservation based charging strategies that include effective reservation management and efficient allocation of time slots of wireless charging stations.

Industry 4.0 or industrial Internet of things (IIoT) has become one of the most talked-about industrial business concepts in recent years. Thus, to efficiently integrate Internet of things technology into industry, the collected and sensed data from IIoT need to be scheduled in real-time constraints, especially for big factories. To this end, we propose in this paper a hierarchical fog servers' deployment at the network service layer across different tiers. Using probabilistic analysis models, we prove the efficiency of the proposed hierarchical fog computing compared with the flat architecture. In this paper, IIoT data and requests are divided into both high priority and low priority requests; the high priority requests are urgent/emergency demands that need to be scheduled rapidly. Therefore, we use two-priority queuing model in order to schedule and analyze IIoT data. Finally, we further introduce a workload assignment algorithm to offload peak loads over higher tiers of the fog hierarchy. Using realistic industrial data from Bosch group, the benefits of the proposed architecture compared to the conventional flat design are proved using various performance metrics and through extensive simulations.

Smart grids (SG) energy management system and electric vehicle (EV) have gained considerable reputation in recent years. This has been enabled by the high growth of EVs on roads; however, this may lead to a significant impact on the power grids. In order to keep EVs far from causing peaks in power demand and to manage building energy during the day, it is important to perform an intelligent scheduling for EVs charging and discharging service and buildings areas by including different metrics, such as real-time price and demand-supply curve. In this paper, we propose a real-time dynamic pricing model for EVs charging and discharging service and building energy management, in order to reduce the peak loads. Our proposed approach uses a decentralized cloud computing architecture based on software define networking (SDN) technology and network function virtualization (NFV). We aim to schedule user's requests in a real-time way and to supervise communications between microgrids controllers, SG and user entities (i.e., EVs, electric vehicles public supply stations, advance metering infrastructure, smart meters, etc.). We formulate the problem as a linear optimization problem for EV and a global optimization problem for all microgrids. We solve the problems by using different decentralized decision algorithms. To the best of our knowledge, this is the first paper that proposes a pricing model based on decentralized Cloud-SDN architecture in order to solve all the aforementioned issues. The extensive simulations and comparisons with related works proved that our proposed pricing model optimizes the energy load during peak hours, maximizes EVs utility, and maintains the microgrid stability. The simulation is based on real electric load of the city of Toronto.

In order to keep Electric Vehicles (EVs) far from causing peaks in power demand during the day, it is important to perform an intelligent management for EVs charging and discharging services by including different metrics in a pricing policy. In this paper, we propose a novel pricing policy for EV charging (G2V) and discharging (V2G) services, in order to reduce the peak load and the energy overflow. Our proposed policy uses cloud computing and smart grid interactions to schedule EV requests. The simulations proved that our proposed pricing policy optimizes the energy load during peak hours and satisfies EVs users and smart grid constraints.

Wireless Sensor Networks (WSNs) have been widely adopted to monitor various ambient conditions including critical infrastructures. Since power grid is considered as a critical infrastructure, and the smart grid has appeared as a viable technology to introduce more reliability, efficiency, controllability, and safety to the traditional power grid, WSNs have been envisioned as potential tools to monitor the smart grid. The motivation behind smart grid monitoring is to improve its emergency preparedness and resilience. Despite their effectiveness in monitoring critical infrastructures, WSNs also introduce various security vulnerabilities due to their open nature and unreliable wireless links. In this paper, we focus on the, Black-Hole (B-H) attack. To cope with this, we propose a hierarchical trust-based WSN monitoring model for the smart grid equipment in order to detect the B-H attacks. Malicious nodes have been detected by testing the trade-off between trust and dropped packet ratios for each Cluster Head (CH). We select different thresholds for the Packets Dropped Ratio (PDR) in order to test the network behaviour with them. We set four different thresholds (20%, 30%, 40%, and 50%). Threshold of 50% has been shown to reach the system stability in early periods with the least number of re-clustering operations.

In this paper the bidirectional power flow between electric vehicle (EV) and grid; Grid-to-Vehicle (G2V) and Vehicle-to-Grid (V2G), is exploited to reduce the negative impact of the huge EV penetration on the current electric networks. We make profit from the unused electric power of EVs and we present an EV load management technique based on EV charging and EV discharging coordination. We propose two algorithms: the first one is the peak load management (PLM) used to schedule EVs for charging or discharging service according to the power demand with the timing and location where each EV need to be served, the second one is the guidance algorithm (GA) used to guide each EV to the appropriate EVSE in the way to reduce its waiting time to plugin. Those algorithms are evaluated while considering mobility of vehicles in an urban scenario and time-of-use-pricing (TOUP). Simulation results show the effectiveness of the proposed approach when considering realistic EVs and charging station characteristics and constraints.

As vehicles get smarter, with supplementary onboard gear providing advanced applications and provisioning services related to traffic management, the requirement for simple and effective access to information has grown extensively. The new applications manage more complex operations and, unlike other mobile devices, mobile vehicle devices provide location based services, real-time functionality, provisioning services and storage, all without the shortcomings of traditional mobile devices. Vehicular cloud computing can perform a broad set of on-demand services and applications, which make this method highly applicable to urban settings. Provisioning services often encounter unexpected interruptions that increase provisioning latency and service usage duration, ultimately leading to higher charges for the driver. This paper advances our previously proposed distributed model to handle service management in vehicular clouds, by using the concept of Vehicular Trusted Third Party (VTTP) with different type of provisioning services. This model has the capability to switch between TTPs, which allows drivers to exploit the benefits of different existing services, and connect to the TTP that best meets their specific requirements. Two new service latency modes are proposed and evaluated: Service Latency Sensitive Mode (SLSM) and Neutral mode. The proposed model has been implemented and evaluated using simulations of real-time light and heavy duty services, and various simulation scenarios show that using a VTTP can significantly help drivers reduce their service latency (~30%) and costs (~26%).

Electric Vehicle (EV) and smart grids have gained much popularity in recent years. This has been enabled by the high increase of EVs on roads; however, this may lead to a significant impact on the power grids. In order to keep EVs far from causing peaks in power demand during the day, it is important to perform an intelligent scheduling for EVs charging and discharging by including metrics, such as price and demand-supply curve. In this paper, we propose a dynamic pricing model for EV charging (i.e., grid-to-vehicle, G2V) and discharging (i.e., vehicle-to-grid, V2G) services, in order to reduce the peak load. Our proposed model uses cloud computing architecture to schedule EV requests. We formulate our problem as a linear optimization problem and solve it using new algorithms for charging and discharging. To the best of our knowledge, this is the first paper that proposes a model that tries to solve all the aforementioned issues. The extensive simulations proved that our proposed pricing model, based on cloud computing and EVs interactions, optimizes the energy load during peak hours and satisfies EVs users and micro grid constraints.

Markov-based analytical modeling has been used extensively to model the operation of the MAC protocol of the IEEE 802.15.4 standard under diverse assumptions. These models reveal the parameters that control the behavior of each node in the network such as end-to-end latency, reliability and power consumption. Focusing on improving a certain metric is highly dependent on the type of application the Wireless Sensor Network (WSN) is designed to support. Although reducing power consumption is a primary design factor in WSNs, the emergence of delay and reliability critical applications such as Smart Grid, healthcare, and the Intelligent Transportation System (ITS) calls for more stringent latency and reliability considerations. In this paper, we develop an optimization model for clustered WSNs to minimize the end-to-end delay and power consumption while maintaining certain levels of reliability. We formulate our optimization problem based on mathematical expressions derived from a Markov-based model. Our results indicate that the lower bounds to expect on latency and power consumption, under constraints on reliability and WSN cluster size, are within the limits required by latency-critical applications.

Monitoring the Smart Grid (SG) is highly desired for critical applications such as power quality assessment and transformer monitoring. Due to their low-cost, flexibility and efficiency as well as their widely usage in several critical infrastructure monitoring applications, Wireless Sensor Networks (WSNs) are estimated to be extensively used in SG applications. WSNs-based SG networks are vulnerable to different types of attacks and intruders. In order to operate networks in secured environments, in this paper we analyze our Clustered Hierarchal Hybrid-Intrusion Detection System (CHH-IDS) that is responsible for various attacks injected by known and unknown intruders. As False Positives (FPs) and False Negatives (FNs) are the key performance parameters in IDS, we investigate mitigation of FNs through a two-tier intrusion detection approach, which deals with anomaly and signature detection in parallel. In the presence of such a hybrid mode, utilization proportion between the anomaly detection and signature detection models affect the FN performance. In these two subsystems, Random Forest method is used for signature detection over known attacks and E-DBSCAN (Enhanced Density-Based Spatial Clustering of Applications with Noise) method is used for anomaly detection over unknown attacks. Through simulations that run on real datasets, we validate that the higher the weight of anomaly detection subsystem (i.e. the lower the weight of the signature detection subsystem), the lower the FN rates experienced by the entire H-IDS system. More specifically, we show that FN rates can be significantly reduced by 20.4% when the weight on anomaly detection subsystem is increased from 60% to 70% while the accuracy is expected to be improved through signature detection subsystem by using the Random Forest which has higher detection rate than the E-DBSCAN method.

The Smart City vision is to improve quality of life and efficiency of urban operations and services while meeting economic, social, and environmental needs of its dwellers. Realizing this vision requires cities to make significant investments in all kinds of smart objects. Recently, the concept of smart vehicle has also emerged as a viable solution for various pressing problems such as traffic management, drivers' comfort, road safety and on-demand provisioning services. With the availability of onboard vehicular services, these vehicles will be a constructive key enabler of smart cities. Smart vehicles are capable of sharing and storing digital content, sensing and monitoring its surroundings, and mobilizing on-demand services. However, the provisioning of these services is challenging due to different ownerships, costs, demand levels, and rewards. In this paper, we present the concept of Smart Vehicle as a Service (SVaaS) to provide continuous vehicular services in smart cities. The solution relies on a location prediction mechanism to determine a vehicle's future location. Once a vehicle's predicted location is determined, a Quality of Experience (QoE) based service selection mechanism is used to select services that are needed before the vehicle's arrival. We provide simulation results to show that our approach can adequately establish vehicular services in a timely and efficient manner. It also shows that the number of utilized services have been doubled when prediction and service discovery is applied.

Vehicular cloud computing can perform a broad set of on-demand applications and services, which makes it highly suitable for urban settings. Despite a wide range of benefits to various services and applications by vehicular clouds, there are several issues and challenges that need to be carefully addressed in the context of provisioning services. This paper proposes a cooperative distributed game model to handle service management in vehicular clouds. Under this model, service providers play a cooperative game to maximize their total utility taking into consideration their recourse availability, current load, and total payoff. The proposed game has been implemented and evaluated using simulations with scenarios of light and heavy weight services. The game demonstrates that a cooperative technique leads players to handle higher number of services when compared to a non-cooperative setting. Furthermore, we also show that the proposed game mimics the behaviour of an optimization-based baseline solution. Through various simulation scenarios, we show that the proposed scheme introduces more than 85% similarity to the optimal solution when a few number of players participate, and its similarity to the optimal solution is improved to 99% when the number of the players increases by only 50%.

The Enhanced Distributed Channel Access (EDCA) and the Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) algorithms are used in the IEEE 802.11p standard to support Quality of Service (QoS) and reliable communication in Vehicular Ad hoc Networks (VANETs). An essential part of the CSMA/CA process is when a packet in an Access Category (AC) waits for an Arbitrary Inter- Frame Space (AIFS) period of time before engaging in the the backoff phase. According to the standard, AIFS values are fixed and deterministic, they do not guarantee strict priority for ACs especially when these values are combined with the Contention Window (CW) size of the backoff phase. On the other hand, the AIFS values are not adjustable, they do not adapt to the current status of the medium. In this paper, we propose two algorithms for AIFS value assignment, the Strict Priority Algorithm (SPA) and the Adaptive AIFS Algorithm (A3). With SPA, the AIFS values are fixed, but they are determined according to a mathematical formula that ensures strict priority level among the ACs. With A3, the AIFS values are adaptively changing depending on the value of the collision probability. AIFS still maintains a strict priority level assignment among the ACs.

The widespread deployment of wireless sensor networks (WSNs) in diverse types of applications motivated the development of strong security measures to protect these networks. The main challenge against deploying strong security algorithms is that WSNs suffer from major constraints in terms of power and computing resources. WSNs impose a primary condition on the design stage that requires any protocol or algorithm to be power-efficient. This means that strong cryptography techniques cannot be used and we need another layer of defence to protect the WSN. This makes intrusion detection systems (IDSs) an essential option in these networks. IDSs can capture malicious misbehaviour that manages to penetrate the first layer of defence (i.e., cryptography and authentication). In this paper we highlight the challenges encountered while designing an efficient intrusion detection framework in WSNs, and provide a review of important contributions in this area. Finally, we propose a new approach that aids in detecting and confining intrusive behaviour in the network.

This paper proposes a Cloud-centric platform offering efficient inventory management as a service for supply chain stakeholders. The offered service will enable all stakeholders in a supply chain to minimize both their ordering costs and their shortage costs, while managing their inventories. The proposed cloud-based platform stores all the data, relating to a given product item, released by the involved stakeholders throughout its life cycle; from its manufacture up to its retail, passing through its distribution, storage, etc. The objective of the offered service is to provide stakeholders, in a supply chain, with efficient replenishment schemes derived collaboratively on the basis of real-time information flow, including retail information. A stakeholder calls the proposed service in order to compute a real-time optimal “inventory threshold”, with regard to a given product category, to be considered in its replenishment policy. By optimal we mean that it minimizes the stock disruption likelihood, while minimizing the allocated resources in term of storage space and inventory cash value. The computation of the optimal parameters is based on a probabilistic model. Analytical results illustrate the efficiency of the inventory optimization service offered by our proposed cloud-centric platform.

Cloud computing is a tremendous opportunity for both enterprises and end users. Cloud users can benefit from the possibility of remote processing in order to outsource their data and infrastructure; that is why many companies have chosen to adopt cloud-deployed solutions such as remote databases, mail servers, and connected applications. However, the cloud fails to provide sufficient security measure to preserve the privacy of the data even from the service providers. Therefore, the research community has assigned to this topic the utmost attention by proposing several solutions like blind processing. This latter is based on homomorphic encryption schemes and allows performing operations on encrypted data without decryption. This way it is possible to protect users' privacy even from the cloud provider since we only publish an encrypted form of the sensitive data. But, most of the proposed solutions only deal with the case of a mono-setting environment where one user collaborates with one server, whereby the multi-user topology reveals another kind of issues such as key sharing and concurrent access. In this paper, we propose a blind decryption technique based on homomorphic encryption that allows not only a user but multiple users to manage the same encrypted data without sharing the secret key. The proposed protocol could be utilized to build various kinds of cloud applications which require the collaboration of several users like remote databases, files sharing, and video-on-demand services.

The digitalization of our day-to-day activities has resulted in a huge volume of data. This data, called Big Data, is used by many organizations to extract valuable information either to take marketing decisions, track specific behaviors or detect threat attacks. The processing of such data is made possible by using multiple techniques, called Big Data Analytics, which allow getting enormous benefits by dealing with any massive volume of unstructured, structured and semi-structured content that is fast changing and impossible to process using conventional database techniques. However, while Big Data represents an immense opportunity for many industries and decisions makers, it also represents a big risk for many users. This risk arises from the fact that these analytics tools consist of storing, managing and efficiently analyzing varied data gathered from all possible and available sources. The consequence is that people become widely vulnerable to exposure because of combining and exploring specific behavioral data. That is, it is possible to collect more data than it should have which leads to many security and privacy violations. Therefore, research community has to consider these issues by proposing strong protection techniques that enable getting benefits from big data without risking privacy. In this paper, we highlight the benefits of Big Data Analytics and then we review challenges of security and privacy in big data environments. Furthermore, we present some available protection techniques and propose some possible tracks that enable security and privacy in a malicious big data context.

The volume of traffic carried on the Optical Transport Network (OTN) is continuously growing, not only due to the increase of new services, new applications, and the number of both connected users and smart devices, but also owing to the rapidly growing Data Center Interconnect (DCI) market. As a result, telecom operators need to upgrade their transport networks to cope with these new traffic requirements. This tremendous increase in bandwidth demand will also introduce energy bottlenecks in OTNs. The telecommunication networks' significant Greenhouse Gas Emissions (GGE) is another challenge that must be addressed in OTN design and planning policies. Thus, energy-efficient OTN architectures are currently attracting the attention of telecom operators. The candidate OTN architectures are: (1) the conventional Dense Wavelength Division Multiplexing (DWDM) fixed grid with high Single Line Rates (SLRs); (2) the conventional DWDM fixed grid adopting Mixed Line Rates (MLRs); and (3) the Elastic Optical Network (EON) or flexigrid-based architecture which is enabled by the Optical Orthogonal Frequency Division Multiplexing (O-OFDM) technique. This paper evaluates the power consumption of the abovementioned OTN architectures under different traffic loads and patterns, as well as different network physical topologies. In order to perform the evaluation, new heuristic algorithms are specifically developed for the green design and planning of data center optical interconnects.

Vehicular-to-Vehicular (V2V) and Vehicular-to-Infrastructure (V2I) communications in Vehicular Ad hoc Network (VANET) environment rely mainly on Medium Access Control (MAC) to minimize the delay and maintain reliable access to the communication medium. IEEE 802.11p standard is developed to achieve these goals. However its performance deteriorates drastically in large networks due to the high level of contention between the vehicles. In this paper, we propose a Quality of Service (QoS) based MAC scheme for high intensity vehicular networks to maintain low delays, high throughput and support QoS provisioning for critical traffic. We develop a model to partition the network into clusters managed by Cluster Heads (CHs), the CHs form a multi-layer architecture where the Road Side Unit (RSU) is located at the root of the tree. We propose a QoS Distributed Time Synchronization (QDTS) mechanism to manage the Time Slot (TS) allocations in a distributed manner. We develop three communication scenarios to evaluate our mechanism in terms of average end to end delay and average throughput. Our results show that our mechanism outperforms the IEEE 802.11p standard, the average end-to-end delay is reduced and the average network throughput is increased.

The Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) is an integrated algorithm employed in the Enhanced Distributed Channel Access (EDCA) in the IEEE 802.11p protocol. CSMA/CA manages the access of packets to the medium and its main role is to avoid collisions among them. An essential process of CSMA/CA is the backoff period in which the packets has to wait for a random number of Time Slots (TS) before attempting to access the medium. The backoff operation is based on a simple deterministic approach that does not consider the status of the medium at the time of transmission. In this paper, we propose an Adaptive Backoff Algorithm (ABA). ABA is based on a probabilistic approach that takes into account the current situation of the medium. ABA is calculated as a function of the packets probability of collision. We present two algorithms ABA1 and ABA2, the function of the former is directly proportional to the collision probability however the function of the latter is exponentially dependent on the collision probability. We develop a Markov-based analytical model to evaluate ABA1 and ABA2, and study the performance of each system.

The ascending increase in the numbers of Plug-in Electric Vehicles (PEVs) in the world brought forward many new challenges to the power grid and utility networks. Some of these challenges are related to finding and managing additional power resources for these PEVs. Green power is one of the alternatives but, we still need to find a cheap way to store this power, PEVs could play a significant role in storing power at a certain time and use it at another time. Never the less, it can play the same role with electric power from grids so it can store power from off peak time to peak time. This role might help the grid to fulfill the growing demands. In this paper, we propose flexible charging and discharging algorithm that effectively addresses and solves the problem of power demand on peak time using the PEV's batteries as a source for backup energy storage. The results show significant enhancement in the power consumption without affecting the performance of electric vehicle.

In a Public Safety (PS) situation, agents may require critical and personally identifiable information. Therefore, not only does context and location-aware information need to be available, but also the privacy of such information should be preserved. Existing solutions do not address such a problem in a PS environment. This paper proposes a framework in which anonymized Personal Information (PI) is accessible to authorized public safety agents under a PS circumstance. In particular, we propose a secure data storage structure along with privacy-preserving mobile search framework, suitable for Public Safety Networks (PSNs). As a result, availability and privacy of PI are achieved simultaneously. However, the design of such a framework encounters substantial challenges, including scalability, reliability of the data, computation and communication and storage efficiency, etc. We leverage Secure Indexing (SI) methods and modify Bloom Filters (BFs) to create a secure data storage structure to store encrypted meta-data. As a result, our construction enables secure and privacy-preserving multi-keyword search capability. In addition, our system scales very well, maintains availability of data, imposes minimum delay, and has affordable storage overhead. We provide extensive security analysis, simulation studies, and performance comparison with the state-of-the-art solutions to demonstrate the efficiency and effectiveness of the proposed approach. To the best of our knowledge, this work is the first to address such issues in the context of PSNs.

With the successful deployment of the fourth-generation cellular networks around the world, long-term evolution (LTE) and LTE-advanced (LTE-A) have become key technologies to enable Internet of Things (IoT) applications. To accommodate various streaming data of IoT applications, LTE/LTE-A standards have defined several quality-of-service (QoS) classes for different traffic characteristics, in terms of traffic bit-rate, tolerable delay, and packet loss rate. Moreover, to meet the stringent power-saving requirements for IoT devices, LTE/LTE-A standards also have defined the discontinuous reception/transmission (DRX/DTX) mechanism to allow devices to turn off their radio interfaces and go to sleep when no data need to be received or transmitted from/to the evolved Node B (eNodeB).

Abstract Wireless sensor networks (WSNs) are getting popular for their deployment in unattended environments, where a registered user can log in to the network and access data collected from the desired sensor. Because of limited resources and computation power in sensor nodes, an authentication protocol should be simple and efficient. M.L. Das proposed a two‐factor authentication scheme for WSNs. Because his scheme uses only one‐way hash function and XOR operation, it is well suited for resource‐constrained environments. Because of some flaws in Das's scheme, several improved schemes have been introduced. In this paper, we show that Das's scheme and its derivatives not only have security imperfections but also do not provide key agreement. To overcome their security shortcomings, we propose a novel user authentication scheme with key agreement for WSN. We furnish security analysis of the proposed protocol to show its robustness to various attacks as well as analyze its performance to determine its efficiency. We provide protocol analysis and verification of the proposed protocol. Compared with the existing schemes, it is more robust and offers better security. Copyright © 2012 John Wiley & Sons, Ltd.

In the cloud era, data centers consume tremendous power due to their huge computing and storage requirements. Furthermore, allocation and release of resources by numerous cloud customers leads to significant energy consumption at the data centers, which in turn, increases the Operational expenditures (Opex) of the operators. In this article, we combine energy efficiency and Time of Use (ToU)-awareness, and propose a novel virtualization scheme, namely ToU-aware Provisioning (ToUP) for an inter-data center network over an IP over WDM backbone. In ToUP, in addition to the traffic between two backbone nodes, upstream user demands destined to data centers and downstream data center demands originating from many data centers; inter-data center traffic is also considered for workload sharing between the data centers. Initially, we present an MILP formulation to model the optimal behavior of ToUP. Since the inter-data center network needs to be reconfigured in polynomial time, we propose a simulated annealing (SA)-based heuristic. We verify the heuristic by using the MILP solution as the benchmark. We evaluate ToUP under various scenarios, and numerical results confirm that significant Opex savings can be achieved while demands can be provisioned with low energy consumption in the data centers and network equipments.

Efficient and scalable information discovery is one of the most important services in any large- scale Internet of Things (IoT) application, particularly in the EPCglobal Network. Although a number of distributed architectures have been proposed in the literature, both their scalability and their lookup time efficiency remain vulnerable, mainly because of their reliance on flat Peer-to-Peer (P2P) Networking. The purpose of this paper is to introduce a hierarchical distributed architecture for EPCglobal Discovery Services, called HEDSA, which improves the scalability and the lookup time of the flat P2P architectures, represented by FEDSA. The idea behind the hierarchy concept of HEDSA is that any Electronic Product Code (EPC) can be mapped to one and only one country, which is the issuing country of the corresponding company prefix. An emulation of FEDSA and HEDSA has been implemented on Planetlab using Chord algorithm, the objective being to compare the scalability and the lookup time of the two architectures. Several experiments have shown that HEDSA is much more efficient, both in terms of the number of hops and the lookup time, than FEDSA. Therefore, HEDSA is more suitable for large-scale IoT discovery services applications, such as the EPCglobal Network, provided that the identifiers can be mapped to one and only one geographical location.

This article studies the impact of Radio Frequency (RF) energy harvesting on the design and performance of cooperative spectrum sensing in Cognitive Radio Networks (CRNs). While recent literature have primarily focused on mode selection and sensing-throughput optimization at the terminal level; this article discusses the challenges of mode selection in infrastructure networks, like IEEE 802.22 and 802.11af, using cooperative spectrum sensing. In particular, we develop two distributed mode selection strategies that cater for the time-varying needs of the network terminals. It is shown that these strategies give adequate flexibility to the network without jeopardising throughput. Computer simulations are used to show the advantages of the proposed strategies compared to the conventional decision-based cooperative spectrum sensing.

Smart grid advanced metering infrastructure (AMI) bridges between consumers, utilities, and market. Its operation relies on large scale communication networks. At the lowest level, information are acquired by smart meters and sensors. At the highest level, information are stored and processed by smart grid control centers for various purposes. The AMI conveys a big amount of sensitive information. Prevention of unauthorized access to these information is a major concern for smart grid operators. Encryption is the primary security measure for preventing unauthorized access. It incurs various overheads and deployment costs. In recent times, the security as a service (SECaaS) model has introduced a number cloud-based security solutions such as encryption as a service (EaaS). It promises the speed and cost-effectiveness of cloud computing. In this paper, we propose a framework named encryption service for smart grid AMI (ES4AM). The ES4AM framework focuses on lightweight encryption of in-flight AMI data. We also study the feasibility of the framework using relevant simulation results.

Plug-in Electric Vehicles (PEVs) are expected to be widely utilized in the near future if issues related to the availability of charging infrastructure are resolved and if PEVs are efficiently integrated with the smart grid. The Vehicle-to-Grid (V2G) system is an emerging technology that enables the communication and control between PEVs and the smart grid. This promising concept is designed to provide the vehicles with information about where and when to charge their batteries, and allows the smart grid to acquire power from a PEV. An essential element to the success of V2G systems is reliable and secure communication system. Wireless communications in highly mobile V2G environment introduce serious challenges, such as reliability and real-time communication. In this paper, we present a comprehensive analysis of the impact of speed on the end-to-end delay and throughput in V2G communication scenarios. We focus on situations where authentication is performed when essential information such as payment data is exchanged between PEVs and its charging infrastructure. Furthermore, we present realistic delay analysis of the proposed communication infrastructure. Our simulation results show the impact of traffic density and speed on both the end-to-end delay and the throughput. We draw recommendations based on our test scenarios and simulation results.

The low-power, low-rate ZigBee wireless sensor networks are vulnerable to the interference of collocated Wi-Fi wireless local area networks (WLAN). The results acquired through our extensive experimental studies on ZigBee-WLAN coexistence indicate that ZigBee connections may experience severe packet losses, caused by combined effect of interference and relatively long receive to transmit (RX-TX) turnaround time in ZigBee devices, even when the Wi-Fi and ZigBee devices are able to detect each other's signal and apply CSMA/CA algorithm accordingly. This paper proposes a novel Adaptive Preamble Padding with Retransmission Control (APPRC) technique for ZigBee devices to address this issue, meet certain packet loss rate (PLR) requirement, and improve packet transmission efficiency when they are suffering time varying interference from the collocated WLAN. The experimental performance evaluation results showed that the proposed APPRC technique can achieve significantly higher transmission efficiency while satisfying PLR requirements of sensing applications than packet retransmission. The technique described in this paper is patent pending.

In Vehicle Ad-hoc Networks, beacon is generated periodically to provide adequate awareness of the surrounding vehicles and environment. Generating periodic beacons at the same rates for all vehicles, typically high rates for safety applications, consume sizeable resources on communication channel. This is in turn presents a challenge to a reliable and successful delivery. This problem gains a lot of attention and researchers started to come up with many fundamentally different solutions to adjust beacons rate for better scalability. However, adjusting beacon rate without a good estimate of beacon data lifetime may impact the accuracy of the awareness of the surrounding vehicles. Particularly, for the applications and protocols that require knowledge about network topology. Accordingly, we propose a new mathematical formula, Adaptive Expiry Time (AET), to determine the lifetime of beacon data. It is independent of beacon scheduling interval and based on neighbour position, speed and orientation. It has been evaluated using proposed Dynamic Beacon Scheduling (DBS) that adjusts beacon interval according vehicle speed. Furthermore, it has been compared to different approaches of expiry time, such as Constant Expiry Time (CET), Variable Expiry Time (VET).

Recent studies have shown that the low-power ZigBee based wireless sensor networks (WSN) are vulnerable to the interference generated by nodes of Wi-Fi wireless local area networks (WLAN). Mutual interference can be mitigated at nodes of either technology when energy detection (ED) is enabled in clear channel assessment (CCA). From our experimental studies on ZigBee and Wi-Fi coexistence issue, it is determined that a significant amount of ZigBee packet losses occur due to the Wi-Fi interference induced corruption of the physical layer header of ZigBee packets, which could happen even when the ED mechanisms of the Wi-Fi and ZigBee devices are able to detect each other's signal and CSMA/CA algorithms are applied accordingly. To study this phenomenon, a series of experiments were carried out, followed by thorough analysis of the recorded data. The study led to the design of a simple but effective technique named Protective Dummy-byte Preamble Padding (PDBPP) that improves the performance of ZigBee packet transmission in terms of packet loss rate (PLR) and transmission efficiency. The experimental performance evaluation results confirmed the effectiveness of PDBPP in improving PLR and transmission efficiency of a ZigBee network exposed to interference generated by collocated WLAN. Some material in this paper is part of a pending patent.

This paper introduces two distributed Bluetooth scatternet formation (BSF) algorithms, called BSFWAVVY(MSF) and BSFWAVVY(ODL). The first algorithm forms scatternets that does not contain master-slave (MS) bridges (MS-free scatternets), whereas the second algorithm forms scatternets in which each piconet has at most k slaves (outdegree-limited scatternets). The motivation is that MS-freeness and outdegree limitation are the two properties that significantly improve the quality of the scatternets. However, and contrary to the existing BSF algorithms, our algorithms consider these properties under pessimistic environments modeled as arbitrary networks (i.e., no assumptions are made on the underlying network topology). We give two lower bounds that prove the asymptotic optimality of our algorithms with respect to time complexity and message complexity. We also show that the problem of forming MS-free and outdegreelimited scatternets at the same time is NP-COMPLETE. We introduce a time-efficient implementation of BSFWAVVY(MSF) and BSFWAVVY(ODL) that exploits unique characteristics of Bluetooth networks. Simulation experiments show that our algorithms have short execution time relative to major BSF algorithms and it outperforms other major algorithms with respect to various performance metrics.

Wireless Sensor Networks (WSNs) have been proposed for various monitoring applications including environmental, industrial, military and health care. The use of WSNs with cluster-tree topologies for such applications solves the limited coverage issue of the wireless sensor devices and allows them to be deployed in wider area. WSNs with cluster-tree topologies suffer from various problems including accurate synchronization of beacons used in the beacon enabled mode in the IEEE 802.15.4 standard and providing Quality of Service (QoS) to delay-aware applications. In this paper, we present a Time Slot Control (TSC) scheme that can adaptively manage the allocation of time slots in the beacon enabled mode of operation to provide QoS grantees to delay critical traffic. Our proposed scheme can improve the end-to-end delay and throughput of selected traffic types by managing the time slots between sensor devices in an optimum way.

Use ol social network services has been more widespread as mobile social network applications have been developed for smart phones. Besides, smart phone sensing, namely Sensing-as-a-Service (S2aaS) provides the front-edge access to the cloud-centric Internet of Things. S2aaS can provide crowdsourced data for several purposes such as public safety, crowd management and environment monitoring. Trustworthiness of crowdsourced data is an important challenge in S2aaS as maliciously altered data can be misleading for the S2aaS customer. Reputation-aware crowdsourcing schemes can address trustworthiness problem however smart phone users moving based on a social network mobility (SNM) model introduce further challenges. In this paper, we propose reputation-and-SNM-aware crowdsourcing scheme which is based on an auction executed at a cloud platform. The cloud platform aims at maximum utility by estimating users' future locations based on their interactions over the social network service so that efficient user-sensing task matching can be done. Furthermore, past and current reputation of the users are taken into account while recruiting smart phone users for given sensing tasks. Our simulations show that reputation-awareness accompanied with SNM-awareness can significantly increase the platform utility by up to 55%. Furthermore, incorporation of reputation-awareness can degrade disinformation probability by more than 70%.

Cloud computing model can enable provisioning of sensing services through mobile phones, namely Sensing-as-a-Service (S2aaS). In this paper, we study S2aaS over social networking services for crowd management problem where malicious users report false sensor readings leading to severe disinformation at the crowd control platform. To this end, we propose Trustworthy Sensing for Crowd Management (TSCM) which is a reputation-based crowd management scheme over the cloud platform where sensing data is collected from smart phones based on an auction mechanism. TSCM periodically runs an auction in order to assign dynamically arriving sensing task requests to the smart phone users forming a crowd connected through a social network. User bids, task values and user reputation values are taken as the inputs whereas the outputs are the utility of the crowd management platform and the average utility per user while reputation of a user is a function of the accuracy of the sensed data. Through simulations, we show that TSCM significantly improves the platform utility while degrading the ratio of the maliciously crowdsourced task by 75%. Furthermore, we also show that under TSCM, reputation of malicious users converge to a low value at the order of 40% following a few auctions.

Cloud data centers are significant players in the electricity market due to their high energy consumption. It is highly desired to operate cloud data centers on only renewable energy such as solar, wind or tidal to reduce their cost and emissions. In the literature, utilization of renewable energy is maximized through workload migration towards data centers that are forecasted to have surplus renewable energy which is also known as “follow the sun chase the wind” approach. In practice, it is rather difficult and unrealistic to shift workloads based on instantaneous output of renewable generation. Generally forecast tools are used which can only provide a rough estimate of the generation capacity. In this paper, we use a more realistic approach and propose an overlay architecture to form energy circles of cloud data centers depending on their load and renewable energy futures contracts. A futures contract is an electricity purchase agreement between the data center operator and the renewable energy generator to purchase electricity in the future with today's price. Futures contracts are electricity market mechanisms that reduce the cost related risks for both parties and are seen as tools to scale-up renewable generation. On the other hand, fluctuating loads of cloud data centers may leave some contract capacity left unused or exceed the capacity. In this case, electricity will be purchased at current market price from the renewable generator or the utility grid where in both cases the electricity bill will increase. Hence, a mechanism to utilize the unused capacity in the contracts of peer data centers and shifting workloads towards available capacity can reduce bills as well as increase the utilization of renewable energy. Our proposed energy circles approach aims to group cloud data centers to achieve those goals.

Wireless Energy Transfer (WET) promises charging wireless sensor networks, cell phones and on-body medical devices without the need of battery replacement nor plugging in to the mains. Magnetic induction and electromagnetic radiation are two alternative technologies for WET. Magnetic induction based WET is a mature technology while electromagnetic radiation based WET has been recently studied for WSNs or RFID tags in many studies. On the other hand, powering cell phones, PDAs or other User Equipment (UE) from ambient electromagnetic signals has unique challenges and is an emerging field of study. In this paper, we consider Radio Frequency WET (RF-WET) for prolonging UE lifetime in a Heterogeneous wireless network (HetNet). In a HetNet, coverage and capacity of the macro cell is augmented by small cells such as picocells, femtocells or Wi-Fi hotspots. In this paper, we assume small cell base stations and dedicated Energy Transmission Towers (ETTs) work together towards supplying power to the UEs. Power is supplied in the same frequency band with the communications in a time-sharing manner. We propose an ILP model where a mix of Picocell Base Stations (PBSs) and ETTs are placed such that the harvested energy is maximized while the number of ETTs and the number of actively power transmitting PBSs are minimized. We show that extended range of PBSs aid in increasing the amount of energy harvested by the UEs while as the number of serviced UEs increase the overall power harvesting capacity of the system improves.

In the Internet of Things (IoT) era, smart devices that are equipped with various types of sensors can enable access to the IoT architecture through a cloud-inspired service model, namely Sensing-as-a-Service (S2aaS). S2aaS can provide crowdsourced data to an application running on a cloud platform. The crowdsourced data can be used for several purposes such as public safety. One of the biggest challenges here is the incentive mechanisms for the users who are requested to provide S2aaS. In this paper, we propose mobility-aware trustworthy crowdsourcing (MATCS) framework in a cloud-centric IoT architecture which adopts and extends a previous scheme, Trustworthy Sensing for Crowd Management (TSCM) [1] by incorporating user mobility-awareness in the presence of maliciously altered sensing data. MATCS employs a user-centric incentive mechanism which collects sensing data based on an auction procedure. In the auction procedure, MATCS uses users' reputations, bids, current location and their estimated dislocation during crowdsourcing process. Furthermore, in order to investigate the benefits of reputation-awareness, we also propose reputation-unaware Mobility-Aware Crowdsourcing (MACS). Performance of MATCS is evaluated via simulations, and it is compared to MACS and a benchmark scheme, which aims at making a compromise between the utilities of the users and the platform by considering neither mobility nor trustworthiness. Simulation results confirm that mobility-awareness improves the utility of the platform significantly whereas combining reputation-awareness and mobility-awareness by MATCS can triple the improvement. Besides, user incomes are not significantly impacted by MACS or MATCS when users are mobile. Furthermore, maliciously altered data ratio can be degraded by 20%~55% by reputation-awareness in MATCS.

In this paper, we present a new protocol for EPC discovery services, namely Delay Tolerant EPC-BGP (DT-EPC-BGP), which is an extension of the previously proposed EPC-BGP. By inheriting all features of EPC-BGP features, DT-EPC-BGP introduces a new mechanism that allows information about the status of the mesh nodes to be exchanged along with other routing information. This new extension sets update sessions with only active nodes, and drops any update request that is destined to an inactive node. We have evaluated DT-EPC-BGP in terms of blocking probability, similarities among routing tables and number of updates in comparison to EPC-BGP. We have shown that DT-EPC-BGP outperforms its predecessor, EPC-BGP by introducing lower blocking probability, lower inconsistency in routing tables among different nodes, and lower number of updates which leads to less control overhead messages.

Vehicular clouds are formed by incorporating cloud-based services into vehicular ad hoc networks. Amongst the several challenges in a vehicular cloud network, virtual machine migration (VMM) may be one of the most crucial issues that need addressing. In this paper, a novel solution for VMM in a vehicular cloud is presented. The vehicular cloud is modeled as a small corporate data center with mobile hosts, equipped with limited computational and storage capacities. The proposed scheme is called Vehicular Virtual Machine Migration (VVMM). The VVMM aims to achieve efficient handling of frequent changes in the data center topology, host heterogeneity, all while doing so with minimum Roadside Unit (RU) intervention. Three modes of VVMM are studied. The first mode, VVMM-U uniformly selects the destinations for VM migrations, which will take place shortly prior to a vehicle's departure from the coverage of the RU. The second mode, VVMM-LW aims at migrating the VM to the vehicle with the least workload, and the third mode, VVMM-MA incorporates mobility awareness by migrating the VM to the vehicle with the least workload and forecasted to be within the geographic boundaries of the vehicular cloud. We evaluate the performance of our proposed framework through simulations. Simulation results show that VVMM-MA introduces significant reduction in unsuccessful migration attempts and results in an increased fairness in vehicle capacity utilization across the vehicular cloud system.

This paper introduces two distributed Bluetooth Scatternet Formation (BSF) algorithms, called BSFWAVVY(MSF) and BSFWAVVY(ODL). The first algorithm forms scatternets that contain no MS-bridges (MS-free scatternets), while the second forms scatternets in which each piconet has at most k slaves (outdegree-limited scatternets). MS-freeness and outdegreelimitation are two properties that significantly improve the quality of the scatternets. Contrary to existing BSF algorithms, our algorithms consider these properties under pessimistic environments modeled as arbitrary networks (i.e. no assumptions are made on the underlying network topology). The optimality of our algorithms are proven. Future directions are proposed to further improve the empirical performance of the introduced algorithms.

Communication technologies are striving to provide ubiquitous and cable-free communication services to users while user devices are still limited with their batteries and need wires to recharge their batteries. The recent advances in Wireless Power Transfer (WPT) are promising to charge wireless sensor networks and on-body medical devices without the need of wires or battery replacement. One natural way of scavenging energy from the environment and providing ubiquitous power is electromagnetic radiation based WPT. Recently powering up Wireless Sensor Networks (WSNs) or RFID tags via omnidirectional radiation and beamforming has been studied in several studies. Yet, the potential of exploiting wireless networks to power User Equipment (UE) such as mobile phones or PDAs has been less explored. Long distances between wireless towers and UEs as well as their relatively low transmit power are among the major bottlenecks for WPT in wireless networks. In this paper, we consider dedicated energy transmission units (DETUs) to provide power to UEs. We show that although certain amount of power can be harvested by UEs, the cost of deploying DETUs dominates the design decision. As a transitional solution, power from relays, small cell towers and WiFi hotspots can be exploited. However when WPT is in-band with information transfer there may be interruption in connectivity. We discuss the challenges of WPT in wireless networks and propose several future directions.

Electric vehicles (EVs) are expected to greatly reduce the carbon emissions from surface transport if they are widely used and efficiently charged. One of the main limitations of EVs is their limited range and relatively long recharging times. This limitation is closely associated with the current battery technologies used in the EVs. In order efficiently utilize the EVs, their charging schedules and locations must be effectively integrated within the smart grid. Real-time and reliable integration of EVs with the smart grid could solve problems related to demand response, cost and time of charging. In this paper, we propose a Quality of Service (QoS) scheme for Charging EVs (QCEV) in a smart grid environment. The proposed scheme provides centralized QoS differentiation to EVs that are communicating with an Access Point (AP) in situations where immediate EV battery charging is required. Our simulation results show that QCEV could significantly improve the performance of the wireless communication network especially in dense deployments.

Wireless Sensor Networks (WSNs) are anticipated to become the preferred tools of choice for monitoring and controlling power utility assets in the smart grid due to their versatility. However, in some smart grid monitoring applications, data generation rates could fluctuate rapidly due to the sudden occurrence of critical faults or failures in the monitored equipment. As a consequence, critical data could experience excessive delays because of this increase in the packet arrival rates. In this paper, we present an Adaptive Guaranteed Time Slot (GTS) allocation scheme (AGTS) for IEEE 802.15.4-based WSNs used in high traffic intensity smart grid monitoring applications. AGTS scheme can adaptively reduce the end-to-end delay and flexibly tune the GTS to provide the required Quality of Service (QoS) differentiation to delay critical smart grid monitoring applications. The proposed scheme can adaptively allocate the needed GTS to nodes transmitting high priority traffic or draw back the unneeded GTS.

The Internet of Things (IoT) paradigm stands for virtually interconnected objects that are identifiable and equipped with sensing, computing, and communication capabilities. Implementation of services and applications over the IoT architecture can take benefit of the cloud computing concept. Sensing-as-a-Service (S2aaS) is a cloud-inspired service model which enables access to the IoT. In this paper, we present a framework where IoT can enhance public safety by crowd management via sensing services that are provided by smart phones equipped with various types of sensors. In order to ensure trustworthiness in the presented framework, we propose a reputation-based (S2aaS) scheme, namely, Trustworthy Sensing for Crowd Management (TSCM) for front-end access to the IoT. TSCM collects sensing data based on a cloud model and an auction procedure which selects mobile devices for particular sensing tasks and determines the payments to the users of the mobile devices that provide data. Performance evaluation of TSCM shows that the impact of malicious users in the crowdsourced data can be degraded by 75% while trustworthiness of a malicious user converges to a value below 40% following few auctions. Moreover, we show that TSCM can enhance the utility of the public safety authority up to 85%.

The articles in this special issue focus on energy efficiency techniques deployed in optical fiber networking.

QoS routing plays a critical role in providing QoS support in the Internet. Most existing QoS routing algorithms employ the strategy of unidirectional search in route selection. Bidirectional search has been recognized as an effective strategy for fast route acquisition in identifying the shortest path connecting a pair of nodes. However, its efficiency has not been well established in the context of route selection subject to multiple additive constraints, which is in general NP-Complete. In this paper, we study how to employ bidirectional search to support efficient QoS routing subject to multiple additive constraints. The major contributions in this paper are as follows. First, we propose a$k$shortest path algorithm using bidirectional search, whose complexity is deduced to be$O(\sqrt{k}\vert V \vert\lg (\vert V \vert) + k\vert E\vert)$, where$\vert V \vert$and$\vert E \vert$represent the number of nodes and links in the network, respectively. Second, we show that bidirectional search can significantly accelerate the convergence of several existing QoS routing algorithms. Third, we propose a novel cost-effective bidirectional multi-constrained routing algorithm, which can greatly alleviate the forwarding state scalability issue by supporting stateless QoS routing in IP networks via IP tunneling or constraints-based alternate routing in MPLS networks via label stacks. It has the fastest known on-line running time$O(\vert V\vert)$. Theoretical and simulation results are given to demonstrate the high performance of our proposed algorithm in identifying QoS-satisfied paths and also in efficient resource utilization as compared with existing algorithms.

Common Radio Resource Management techniques have shown great promise in both enhancing network operation and user satisfication.Such gains are achieved through the joint management of the individual access technologies in a Heterogeneous Wireless Network.The objective of this work is to expand on the existing body of work to accommodate heterogeneity not just at the traditional access-network level but to other connectivity modes such as dynamic spectrum access.Such modes affect operator profitability in both the long and short terms.Specifically, we explore the design of a cost-management model that adapts to the short-term variability in connectivity costs.We also display the operational aspects and effectiveness of this functionality through both simulation and an analytical model.

Recent studies have shown that low-power ZigBee based wireless sensor networks (WSN) are vulnerable to the interference generated by Wi-Fi nodes. In this study, the effects of energy detection (ED) mechanism in clear channel assessment (CCA) of ZigBee transmitter under 802.11g Wi-Fi interference have been evaluated through experimentation. To improve the performance of ZigBee packet transmission, a preliminary adaptive mechanism is implemented and evaluated in our testbed.

The use of Wireless Sensor Networks (WSNs) to monitor and control power utility assets in the smart grid is gaining increasing popularity due to their various desirable features. WSNs with multihop cluster tree topologies solve the limited coverage problem of sensor nodes. However, in smart grid monitoring applications, data rates could increase suddenly due to the occurrence of critical faults in the monitored environment. Critical data transmission could experience excessive delays because of this increase in the packet arrival rates. Therefore, there should be an optimum operating point in the network where the network could handle high packet arrival rates and maintain low latency at the same time. In this paper, we present an optimization scheme that can achieve low latency while maintaining high reliability values. Furthermore, we design our scheme to provide Quality of Service (QoS) differentiation to high priority and delay critical data. Results show that our proposed scheme significantly reduces the delay while providing high reliability and incurring low energy consumption.

Cloud computing offers the flexibility of accessing to a shared pool of resources based on the pay as you go fashion. Data centers, being the main hosts of cloud services, play the key role in the delivery of cloud services while energy consumption and resiliency are two main drivers of the operational expenses of the operators. In this paper, we consider the interconnection of cloud data centers over a wide area network, namely the US National Backbone, via IP over elastic optical transport medium. Initially, we present a numerical model to analyze the outage probability of various demand types such as down-stream data center, upstream data center and data center-to-data center demands. Then, we propose two provisioning schemes, namely, Minimum Outage Probability Provisioning (Min-OPP) and Resilient Provisioning with Minimum Power Consumption (RPMPC) where the latter is an extension of the former incorporating energy-awareness. Through numerical results, we show that energy-awareness in the resilient design reduces the power consumption in the cloud backbone by approximately 7% when compared to Min-OPP with significantly lower (45%∼97%) outage probabilities for data center demands when compared to a naïve energy-minimized provisioning. Furthermore, RPMPC introduces shorter path delays which are not higher than those introduced by Min-OPP.

Certain Wireless Sensor Network (WSN) applications such as patient monitoring, smart grid, and equipment condition monitoring require accurate estimation of specific WSN parameters such as end-to-end delay, reliability and power consumption. The estimation of these parameters calls for an accurate and lightweight WSN model that is suitable for the low processing capabilities of sensor nodes. In this paper, we present a Markov-based model for WSNs that considers the impact of inserting a MAC-level finite buffer on the performance of WSNs. We perform a comprehensive performance analysis of the end-to-end delay, reliability and power consumption using different traffic and network conditions in star and cluster-tree WSN topologies. Furthermore, we test the accuracy of our model by conducting extensive simulations in environments that are consistent with the analytical model.

Energy consumption in the residential sector is a considerable source of a wide range of environmental problems. It has been mentioned that the energy consumption in this sector represents 46% of total energy consumption and 23% of greenhouse gas emissions. Technology and services can help consumers manage the energy generated by their renewable or traditional electric grid. Service oriented architecture (SOA) has recently become very popular. SOA is an approach to build distributed systems that deliver application functionality as services to end-user applications or to build other services We adopt an approach to formulate the problem of managing energy in the building in a general form of linear programming by optimizing three criteria: environmental, economic and user comfort. First, we formulate this problem into an integer linear programming (ILP) problem. A round-up heuristic algorithm which is based on linear programming relaxation is presented.

The EPCglobal Network is a global network developed to ensure global interoperability between trading partners in supply chains. Its main goal consists of providing real-time and accurate traceability of items in the supply chains. One of the major building blocks of the EPCglobal Network is the Object Naming Service (ONS) which is a central lookup service used mainly to locate the EPC manager information sources of a given EPC. Discovery services refer to a suite of services enabling any user, subject to authentication, to retrieve all relevant data, subject to access control policies, related to a given EPC in the EPCglobal Network. Many promising DHT-based distributed and secure architectures have been proposed to make the ONS more scalable and more secure than the current ONS specifications. Some of them focused on improving a specific aspect of the existing ONS architecture while others suggested integrated solutions for various weaknesses of the current ONS system. In this paper, we present a DHT-based, scalable and secure architecture for data lookup in the EPCglobal Network. The proposed architecture aims at replacing the current ONS system with a secure distributed Discovery Services system.

We introduce distributed algorithms for the RFID coverage problem, which is defined as finding the minimum amount of RFID readers that cover every tag. The algorithms depends on rounds of writes and reads in/from the tags' memories. The first algorithm, called Greedy Distributed Elimination (GDE), is inspired of, and equivalent to, the greedy approximation algorithm of the set cover problem. Our second contribution is a randomized algorithm that can run in one or more write/read rounds (called RANDOM and RANDOM+). Using concepts concluded from these algorithms, we introduce algorithm GDE-RANDOM+ which improves further the number of non-redundant readers of GDE by integrating it with RAN-DOM+.

Cloud computing is the leading edge concept which combines the advantages of several existing computing concepts for the betterment of the Information and Communication Technology (ICT) business. This new business model aims at moving the services such as software, platform and/or infrastructure to a shared pool of resources which are mainly housed in the data centers. In this paper, we propose a novel virtualization scheme for the cloud network with the objective of provisioning the demands among the data centers in a Time-Of-Use (ToU) pricing-aware manner while ensuring maximum energy savings in the cloud network throughout the day. In addition to the unicast demands between backbone nodes, upstream user demand destined to data centers, and downstream data center demands originating from many data centers, here, we also consider inter-data center traffic in order to enable workload sharing between the data centers. Through numerical results, we show that significant savings in terms of operational expenditures (Opex) can be achieved while demands can be provisioned with less energy consumption in the data centers and network equipments. Furthermore, we show that incorporation of inter-data center workload sharing in ToU-aware provisioning can mitigate the increased propagation delay introduced to the user demands submitted to the cloud.

In this paper, we propose an extended architecture of the EPCglobal network that allows tracking objects. This architecture makes use of the distributed discovery services along with the EPC-BGP to provide detailed information about an object regardless of its location. In the EPCglobal network, each object is assigned an IPv6 address once it leaves the last gateway in the supply chain. The IP address of the last gateway enables backtracking of all the information about this object throughout the supply chain. To this end, EPC status updates are crucial in order to advertise any changes in the EPC into the supply chain. On the other hand, concurrent EPC updates, expired EPC databases and/or limitation of resources may cause blocking of an EPC update request. Therefore, we evaluate our proposed architecture in terms of blocking probability of the EPC update requests. To this end, We define three types of blocking, namely the Justified Update Blocking (JUB), Unjustified Update Acceptance (UUA), and Unjustified Update Blocking (UUB). We investigate the impact of the frequency of update advertisements on the blocking probability. Numerical results confirm the trade-off between blocking probability and communication/computation overhead due to EPC update messages. However, further investigation in terms of the number of advertisements and the distance between the routing tables confirms that advertisement of EPC update messages based on certain thresholds can overcome this trade-off.

In critical infrastructure monitoring applications, the packet arrival rates of a Wireless Sensor Network (WSN) may abruptly increase when cascaded failures are observed in the monitored environment. WSNs with cluster-tree topologies could experience excessive delays because of this increase in packet arrival rates. Therefore, there should be an optimum operating point in the network where the network could accommodate high packet arrival rates with low latency. In this paper, we propose an adaptive scheme that can achieve low latency while maintaining high reliability values in cluster-tree based WSNs. Furthermore, our scheme provides Quality of Service (QoS) differentiation to high priority data. Analytical and simulation results show that our scheme significantly reduces the delay while maintaining high reliability and energy efficiency values.

The mobile networks are continually evolving in order to support more users, to achieve higher data rates, and to provide new (multimedia) services. The next generation networks must be able to service heterogeneous traffic with diverse quality of service (QoS) requirements. Orthogonal frequency division multiple access (OFDMA) is important techniques for high data rate wireless multiuser communication systems, such as 3GPP Long Term Evolution (LTE) and IEEE 802.16 Worldwide Interoperability for Microwave Access (WiMAX), not only because of its flexibility in resource allocation, but also because of its ability to exploit multiuser diversity. The scheduling algorithms that both support the QoS and maintain the throughput required to ensure users' satisfaction are essential to the development of the next network generation. In this paper, different scheduling techniques were evaluated using OFDMA in several different scenarios. The goal is to analyze the properties of networks such as throughput an fairness.

Ultra-wideband (UWB) has attracted a lot of attention in the past few years. UWB offers several advantages over traditional narrow band. Transmitted reference (TR) receivers have been known for many decades, but there is a renewed interest for applications of TR receivers as a suboptimal solution for UWB communications because of the difficulty in estimating the channel accurately for an optimal solution. In this paper, the performance of a UWB-TR receiver in an UWB underground mine channel is evaluated. The performance at higher data rates in the case of inter-symbol interference (ISI) is also investigated.

Energy routing has not been feasible in the traditional power grid due to real-time nature of the electrical services. Electricity is generated and used almost in real time where the balance between the two is maintained by regulation services. Additionally, small number of fixed storage units are utilized to store some portion of the generated energy. In the future electricity grids, Mobile Energy Buffers (MEB) together with local energy buffering capabilities, will be the enabler of energy routing. In this paper, we propose an energy routing framework for low and medium voltage electricity distribution systems that house prioritized MEBs, local buffers and Delay-Tolerant electrical Loads (DTL). We model the distribution system as a token-based system where energy transfer between MEBs and local storage units rely on the availability of tokens that are generated by DTLs. Coordination of token advertisement, storage interest and token access is maintained by machine-to-machine communications. The underlying communication technology can be PowerLine Communications (PLC) or a medium-range wireless communication technology. We provide a mathematical analysis of the token-network with DTLs and prioritized MEBs. We show that coordination and prioritization allow lower blocking rates for high priority MEBs. Our analysis provides valuable insights for utility planning decisions.

Despite its great promises, current Cloud offering is still typically rather static and does not support very dynamic execution patterns. In fact, while dynamic resource allocation is typically required to ensure efficient and effective usage of the Cloud resources, Cloud providers have to deal with complex services, usually treated as black-boxes; hence, the estimation of the maximum number of resources that could improve service execution is a big challenge. This paper proposes and explores a novel automatic service rescaling approach to solve the deployment scaling problem. The proposed scheme, called Dynamic Cloud Infrastructure (DCI), has been designed and verified as a new architecture for the IBM Cloud infrastructure. DCI provides hints useful to understand if a particular service could take full advantage from additional resources enabling automatic discovery of the deployment configuration that jointly addresses high service scalability and low resource consumption. We detail the lessons learnt from the application of the proposed solution in the IBM Smart Bay project and present experimental results that demonstrate our approach as a viable first step toward run-time service scaling.

We introduce a new time-efficient Bluetooth Scatternet Formation (BSF) algorithm, called BSF-UED (Unnecessary-Edges Deletion). BSF-UED forms connected scatternets deterministically. Heuristics are added to make these scatternets outdegree limited (that is, with no more than 7 slaves per piconet). The performance of the algorithm is evaluated through a range of simulation experiments. BSF-UED is compared against some of the most common BSF algorithms which are BlueStars, BlueMIS I, BlueMIS II, and BlueMesh. We show that BSF-UED provides a good balance between the usual scatternets performance metrics, while being time efficient (nearly 1/3 of the execution time of BlueMesh). BlueStars remains a faster algorithm, but with the major flaw of generating scatternets whose piconets have a large number of slaves.

The Quality of Service (QoS) in smart grid communications especially in monitoring smart grid assets is becoming significantly important for emerging smart grid applications. Wireless Sensor Networks (WSNs) are expected to be widely utilized in a broad range of smart grid applications due to their numerous advantages along with their successful adoption in various critical areas including military and health. WSNs protocols are not designed to provide QoS provisioning for monitoring applications. Thus, the use of WSNs in transmitting delay-critical data from smart grid assets calls for data prioritization and delay-mitigation schemes. In this paper, we propose a delay-responsive, cross layer scheme with linear backoff (LDRX) mechanism to address delay and service requirements of the smart grid monitoring applications. The LDRX scheme is designed to operate in cluster-tree WSN topology that is suitable for monitoring wide areas such as electrical substations or large installations. We show that LDRX has greater impact on delay reduction compared to previously proposed WSNs delay reduction schemes.

There has recently been a considerable amount of research work on using data compression techniques to minimize the volume of transmitted traffic, and consequently assist in reducing power consumption levels in Wireless Sensor Networks. In this paper, we present a data Oriented approach called Modelbased Clustering (MBC) which shrinks the communication flows between sensor nodes and sink node in a way that contributes to reducing power consumption in wireless sensor networks. The proposed work utilizes the capabilities of mixture-model based clustering to exploit both the temporal locality and slowly varying properties of the sensed data to model the sensor network's traffic. The generated models will be utilized by both the sensor nodes to process the sensed raw measurements and sink node to recover the original data without requesting those data to be completely transferred by the limited resources' sensor nodes. Results show that our approach contributes to decreasing energy consumption in resource-limited sensor network.

A new connectivity metric is proposed for cognitive radio networks. The analysis is developed based on a generalized model for cognitive radio networks where multiple primary users with independent activity factors are considered. The adjacent matrix elements, representing the weights associated to the network graph edges, are set proportional to the activity factors of primary users. It is shown that the proposed connectivity metric is a monotonically decreasing measure with the primary users activity factors. Furthermore, the metric efficiently determines the network connectivity under different primary users activities. The proposed connectivity metric is compared to the probability of finding a route metric which is commonly used as a measure for network connectivity. It is shown that the proposed metric captures the behavior of the probability of finding a route method with significant complexity reduction. Compared to the algebraic connectivity metric, the proposed metric is more robust in the presence of isolated nodes. Finally, the proposed metric can be utilized to analytically study and design cognitive radio networks.

The low-power, low-rate ZigBee/IEEE 802.15.4 wireless sensor network (WSN) is vulnerable to the interference from a collocated wireless local area network (WLAN), which operates with considerably higher power in the same 2.4GHz Industrial, Scientific, and Medical (ISM) band. In this paper, a novel and effective Interference Aware Adaptive Clear Channel Assessment (IAACCA) technique is proposed to countermeasure the presence of interference with consequence to improve the performance of packet transmission between ZigBee nodes. The performance evaluation has been done through experimentation performed on a testbed implemented by the authors.

With the advent of cloud computing, storage and computing functions are migrating to remote resources such as virtual servers and storage systems which are mostly hosted in the data centers. This migration can ensure significant energy savings as utilization of local resources contribute to 40% of the Greenhouse Gas emissions of the Information and Communication Technologies (ICTs). On the other hand, provisioning of the cloud services needs to be handled carefully since energy consumption of the transport network, as well as the energy consumed by the data centers, is expected to increase. We revisit our previously proposed Mixed Integer Linear Programming (MILP) models that are used to reconfigure the cloud network design with look-ahead demand profile. Due to long runtimes of the MILP models in large-scale scenarios, in this paper, we propose two heuristics to reconfigure the cloud network for provisioning the cloud and Internet computing demands. The first heuristic aims to minimize the propagation delay while the second one targets minimizing the power consumption of the data centers and the transport network. We verify the heuristics through simulations where MILP models are used as the benchmarks. Numerical results show that power minimized provisioning can guarantee significant energy savings in the cloud network with less resource consumption. We also present the energy versus delay trade-off and point out possible solutions.

Cloud computing is becoming a leading edge business model by migrating the resources such as software, storage and platform to remote locations in the Internet cloud. Data centers, as the main hosts of these cloud services, receive massive amount of demands and transmit services towards Internet routers, consequently consuming enormous bandwidth in the downstream. Due to high computing power, as well as the cooling power, data centers contribute to a significant amount of the power consumption and the operational expenditures (Opex) of the data center operator. In the Internet backbone where the services are transported between the users and the data centers, IP routers make the dominating portion of the power consumption and Opex associated with the network operator. In this paper, we study the impacts of Time of Use (ToU)-awareness on the Opex and energy-efficiency of the cloud network by introducing a Mixed Integer Linear Programming (MILP)-based design scheme for the cloud backbone, which aims at minimizing the network and data center power consumption. Furthermore, the optimization scheme takes advantage of the varying ToU rates in different locations of the cloud network so that Opex is minimized for the network and data center operators. Numerical results approve that Opex savings through ToU-aware provisioning are at the expense of increased delay per demand. Furthermore, by the end of the day, power-minimized provisioning introduces more savings to the network operator as upstream data center demands are transported towards the data centers at the off-peak locations, which in return leads to higher utilization of network components in longer routes.

Information and Communication Technologies (ICTs) are contributing to a large amount of the global electricity consumption. Due to tremendous increase in the bandwidth demands and utilisation of non-renewable energy resources Greenhouse Gas Emissions are increasing proportionally with the increasing demand. Despite their advantages in terms of computing performance, distributed applications such as computational grids are major factors that increase the traffic volume in the Internet. In this paper, we propose a distributed framework to ensure energy savings in the optical WDM backbone which transport the traffic between nodes and several computational grids based on anycast routing. According to the proposed framework, the backbone nodes go to sleep mode and resume active mode in a distributed manner with the objective of maximum energy savings in the backbone. Each node maintains two thresholds which are adaptively adjusted based on the network performance, and these thresholds play the key role in determining the decision of a node whether to sleep or resume. Numerical results confirm that the proposed framework can ensure significant energy savings in the network when compared to the conventional energy-unaware operation mode. We further show that the adoption of the proposed network framework does not degrade significantly the network performance in terms of average blocking probability and end-to-end delay.

A Smart Grid is the modernization of the electricity grid using communication technology with the prime goals of reducing energy consumption as well as cost increasing reliability and creating new services for all participants. It comprises key components such as Advanced Metering Infrastructure (AMI) that includes Neighborhood area network (NAN). When multi-hopping is considered in wireless communication, especially in WiFi and ZigBee, the range of communication can be extended to communicate with the gateway collector in AMI network. Wireless mesh AMI network may have smart meters, NAN gateway, and fixed as well as mobile repeaters. Though many techniques have been developed to secure on-demand routing protocols in wireless multi-hop ad hoc networks, these protocols have shortcomings. In this paper, we propose an efficient and robust security mechanism for multipath routing protocol in wireless mesh AMI networks. We have analyzed its robustness to various attacks. The simulation results show that the proposed mechanism is better than existing secure routing protocols.

Wireless Sensor Networks (WSNs) provide wide reach and coverage at low-cost which enable them to be utilized in various fields such as health, smart grid, industrial facilities and defense. One of the fundamental limitations of WSNs in long-lasting applications is the network lifetime. To overcome the battery constraint of sensor nodes, duty cycling, energy-efficient protocols and energy harvesting have been considered widely in the literature. A recently emerging energy harvesting technique, namely Radio Frequency (RF)-based wireless energy transfer promises to extend the lifetime of Wireless Rechargeable Sensor Networks (WRSN) with no dependency on intermittent ambient energy resources. In RF-based wireless energy transfer, deploying power transmitters to fixed locations is costly due to range limitations of wireless power. For this reason, mobile power transmitters that visit a few selected locations; i.e. landmarks are employed. Furthermore, in WSNs sensors are expected to perform certain tasks or missions during their lifetime. The achievement of each mission provides certain profits. In this paper, we aim to optimally select the landmarks for sensor nodes that participate in profit maximizing missions. We propose an Integer Linear Programming (ILP) model, namely Mission-Aware Placement of Wireless Power Transmitters (MAPIT) that optimizes the placement of RF-based chargers in the WRSN by maximizing the number of nodes receiving power from a landmark and those that contribute the maximum profit by achieving a mission. We show that the profit increases for low landmark limit since the number of nodes receiving power from a landmark increases under less landmarks. On the other hand, profit reduces by increased number of missions since the nodes participating to missions become spatially diverse.

We present in this paper three Bluetooth Scatternet Formation (BSF) algorithms which forms deterministically connected and outdegree limited scatternets. Our algorithms improve the execution time of algorithm BlueMIS, which consists of two consecutive phases called BlueMIS I and BlueMIS II. The first phase, BlueMIS I, is a BSF algorithm that forms connected and outdegree limited scatternets in a time-efficient manner. Our algorithms improve BlueMIS by improving BlueMIS I. First, we introduce a time-efficient implementation of communication rounds, called OrderedExchange, that is more suitable for Bluetooth networks, where in a communication round each node sends and receives a message to and from all its neighbors. Using OrderedExchange, we introduce algorithms ComputeMIS I and ComputeMIS II which form the same scatternet as those formed by BlueMIS I but with less execution time. We also introduce algorithm Eliminate. Instead of letting each node u forms a maximal independent set of all its neighbors and then considers them as slaves, as in the case of BlueMIS I, Eliminate let each node u forms a maximal independent set of all its neighbors that have smaller identifiers. Eliminate forms scatternets that are similiar to those formed by BlueMIS I, and more efficient with respect to some performance metrics. Eliminate improves the execution time of ComputeMIS I and ComputeMIS II by about 60%.

Cloud computing calls for efficient solutions to manage the energy consumption of the transport, process and storage services. Recently, we have shown that energy savings in the cloud network and the data centers are at the expense of increased delay; hence degraded service quality. In this paper we propose a new scheme, Delay and Power Minimized Provisioning (DePoMiP) to address energy versus delay tradeoff in the cloud network. DePoMiP reconfigures the cloud network and provisions the demands by jointly minimizing the energy consumption and propagation delay. Through simulations, we compare DePoMiP to our previously proposed heuristics for delay-minimized provisioning and power-minimized provisioning of the demands. Simulation results show that DePoMiP mimics power-minimized provisioning in terms of power consumption while it provisions the demands with a few microseconds higher propagation delay when compared to delay-minimized provisioning. Furthermore, its low channel utilization in the IP over WDM transport network, as well as its fairness among the nodes in terms of power consumption, makes DePoMiP a promising solution for the problem of energy-efficient reconfiguration of the cloud network.

In the cloud computing era, virtualized data centers are expected to host most of the cloud services such as computation, storage and multimedia applications. Cloud services are expected to be transported over the Internet backbone based on anycast/manycast paradigms between the users and data centers. In this paper, we present an optimization model which aims at reconfiguring the cloud network topology so that the delay of cloud service provisioning is minimized without disrupting the service quality of regular Internet services. We compare the performance of the proposed model to the delay performance of an optimization model which aims at minimizing the operational expenditure of the operator. Through numerical results, we show that the proposed optimization model is capable of assuring minimum delay guarantee for the traffic demands destined to/from the data centers, as well as the traffic demands destined to/from the core nodes of the cloud network. Furthermore, we study the overheads and challenges of delay minimized reconfiguration of the cloud network. Numerical results confirm that minimum delay objective does not introduce significant overhead to the data centers in terms of operational expenditure, namely power consumption. On the other hand, we show that the increase in the power consumption of the network equipment in the cloud backbone arises as an important challenge of the presented optimization model.

Significant portion of the energy consumption of the optical networks is expected to be in the transport segment. Besides its improved bandwidth utilization advantage, multi-granular switching concept further helps rectifying the energy bottleneck problem in the backbone. One of the important challenges faced by the multi-granular optical networks is the optical reach enforcement. In this paper, we compare the multi-granular optical network design to the conventional Wavelength Division Multiplexing (WDM)-based network design by enforcing the optical reach limitation as a design constraint. We introduce the heuristics to solve the Routing and Multi-Granular Path Assignment (RMGPA) problem. Our simulation results show that multi-granular optical network design outperforms the WDM-based network design in terms of Operational Expenditure (Opex) as it significantly reduces the power consumption in the backbone. Furthermore, through simulations, we show that the green multi-granular design is efficient in terms of the Capital Expenditure (Capex) as the network cost is also degraded.

Radio Frequency Identification (RFID) technology is promising technology in ubiquitous computing area. RFID is used for various applications, ranging from inventory systems to supply chain management solutions such as vehicle fleet management. In supply chain management system, RFID tag is used to identify the object, to which it is attached, without any physical contact in various locations. This makes tags susceptible to information leak. Thus security and privacy issues remain a major issue. Suitability of public key cryptography solutions in RFID system is open research problem. In recent years, practicability of asymmetric cryptography on RFID applications has been discussed. Though EC-GPS scheme allows compact implementation on a tag, it has several flaws. In this paper, we propose robust RFID authentication scheme for supply chain process using improved EC-GPS. We have provided security proof, security analysis and performance evaluation of the proposed scheme to show its robustness.

In an infrastructure-less wireless ad hoc or sensor network, communication may be achieved between mobile nodes without a central entity (base station) using a half-duplex Slotted ALOHA protocol. The probability of success and the throughput per mobile node can be reduced significantly, if the network is attacked by jamming signals. Mitigating the effect of jamming signals using multi-packet transmission (MPT) and/or multi-packet reception (MPR) capabilities of each mobile node is studied. The effect of the probability of success reduction due to jamming signals can be mitigated by using the MPT and the MPR capabilities of each mobile node. Similarly, reduced throughput can be increased using the same techniques. The maximum throughput per mobile node can be obtained by the proper adjustment of the transmitting probability of each mobile node and the receiving probability of each mobile node. A lower mitigation of the maximum throughput reduction can be obtained by using only the MPT, if the jamming signal rate is very low. On the other hand, only the MPR capability can provide a lower mitigation of the maximum throughput reduction. The effect of jamming signals on the maximum throughput can be mitigated successfully at all traffic load conditions, if the MPT and the MPR capabilities work together.

To avoid huge data loss in the last mile of Internet service, Passive Optical Networks (PONs) need to be designed with a high availability guarantee. Because next generation PON includes extending the coverage of optical broadband access networks under the name long-reach PON, availability-guaranteed planning of PONs for long-reach access is required. In this paper, we propose a Mixed Integer Linear Programming (MILP)-based approach, and a heuristic algorithm, for the planning of survivable long-reach passive optical networks. The MILP-based planning model mainly consists of cost and availability constraints, while having the objective of largest possible area coverage. The heuristic is called Locate-ONU-with-Lowest-Availability-Requirement-First (LOWLARF), and it performs a faster search for the nearly optimal locations of Optical Network Units (ONUs), Optical Line Terminal (OLT), and the optical splitter having the same objective and constraints with the MILP model. The proposed heuristic and the MILP model are compared in terms of the solution spaces provided for a small sized problem. The heuristic LOWLARF introduces the advantage of significantly degraded running time, and numerical results indicate that it can provide close results to those of the MILP-based planning. On the other hand, three survivability schemes are compared in terms of deployment cost, availability, and coverage by MILP-based planning and LOWLARF. The evaluation is done by two different availability requirement scenarios. The results show that, under both scenarios, the protection scheme offering a lower bound of 99.999% availability leads to the highest deployment cost while it covers the smallest area. The protection schemes that guarantee 99.99% availability by employing less redundancy can cover a larger area under both scenarios.

Sensor network web services have recently emerged as promising tools to provide remote management, data collection and querying capabilities for sensor networks. They can be utilized in a large number of fields among which Demand-Side Energy Management (DSEM) is an important application area that has become possible with the smart electrical power grid. DSEM applications generally aim to reduce the cost and the amount of power consumption. In the traditional power grid, DSEM has not been implemented widely due to the large number of households and lack of fine-grained automation tools. However by employing intelligent devices and implementing communication infrastructure among these devices, the smart grid will renovate the existing power grid and it will enable a wide variety of DSEM applications. In this paper, we analyze various DSEM scenarios that become available with sensor network web services. We assume a smart home with a Wireless Sensor Network (WSN) where the sensors are mounted on the appliances and they are able to run web services. The web server retrieves data from the appliances via the web services running on the sensor nodes. These data can be stored in a database after processing, where the database can be accessed by the utility, as well as the inhabitants of the smart home. We show that our implementation is efficient in terms of running time. Moreover, the message sizes and the implementation code is quite small which makes it suitable for the memory-limited sensor nodes. Furthermore, we show the application scenarios introduced in the paper provide energy saving for the smart home.

Optical WDM networks can be employed as the transport medium technology for cloud computing services since they have high capacity and low delay, and they satisfy the service requirements by the help of the control plane. Recent research has shown that cloud services can be efficiently provisioned based on anycast or manycast paradigms. In this paper, we focus on the energy savings in the optical transport network which forms a communication infrastructure for the cloud services based on the manycast paradigm. We propose an optimization model to maximize the energy savings by putting the wavelength routing modules of the optical nodes in the power saving mode. Based on the optimization model, we propose an evolutionary algorithm, namely the Evolutionary Algorithm for Green Light-tree Establishment (EAGLE) which can provide lower runtime for large topologies and find a suboptimal solution. We evaluate the performance of our optimization model by running EAGLE under a topology lying on four different time zones, i.e., NSFNET. Simulation results verify that selecting a feasible number of nodes to put their wavelength routing modules in the power saving mode leads to significant energy savings in transportation of the cloud services over WDM networks. Furthermore, the proposed scheme does not introduce a resource consumption penalty when compared to the wavelength minimizing approach.

The IEEE 802.15.4 standard utilizes the Binary Exponential Backoff (BEB) algorithm to control nodes' access to the shared wireless medium. The main drawback of BEB is that it updates the size of the contention window (CW) without taking into consideration the number of competing nodes and the conditions in the communications medium. Therefore, BEB has been shown to be inefficient in terms of channel utilization and fairness among the contending nodes. In this paper, we propose Adaptive Backoff Algorithm (ABA), a new backoff algorithm that adaptively determines the appropriate size of CW based on the collisions experienced by the nodes. That is, while BEB updates CW in a deterministic fashion, we introduce a probabilistic methodology to achieve that update. Our simulations compare the performance of ABA with that of BEB as well as three other algorithms proposed in the literature, namely, NO-BEB, KEB, and IBEB. The performance is studied in terms of power consumption, reliability, and channel utilization. Our results show that ABA outperforms the aforementioned algorithms while granting each node a fair access to the wireless medium.

Plug-in electric vehicles (PEVs) reduce greenhouse gas emission by using power from the electric grid. PEVs are considered distributed energy resources and mobile storage devices, which require two-way communication standards to communicate with emerging Smart Grid infrastructure. Due to frequent mobility of PEVs, inter-utility real-time data communication is critical to the operation of interconnected systems in Vehicle-to-Grid (V2G) infrastructure. Interoperability and security considerations of V2G infrastructure components are decisive for widespread deployment of PEVs. In this paper, we propose multi-domain network architecture for V2G infrastructure which includes comprehensive hybrid public key infrastructure using hierarchical and peer-to-peer cross-certifications. We present system and performance analysis of the proposed security architecture.

Due to the broadcasting nature of wireless sensor networks, it is relatively easy for an adversary to discover the sinks' location through traffic volume analysis. Traditional encryption and authentication methods are not effective to preserve privacy of a sink's location from a global adversary, capably of monitoring the traffic activity of the network. In this paper, we propose the Sink Location Privacy Protection Protocol (SLPP), which in addition to been effective in achieving its design objective it is also easy to implement. In order to confuse a local or global adversary, each node generates fake messages, the number of which is dependent on the number of the node's children. Simulation results demonstrate clearly that the SLPP protocol can hide effectively the sink's location. However, what is important and interesting is that although transmission of fake messages consumes additional energy from nodes, the network's lifetime is not impacted.

The strict resource-constrained conditions under which Wireless Sensor Networks (WSNs) operate impose primary restrictions on power consumption. Algorithms implemented on sensor nodes should refrain from performing complex computations in order to prolong the lifetime of the overall WSN. The IEEE 802.15.4 standard is the appropriate suite of specifications that conforms to the distinguished characteristics of WSNs. This standard is suited for low data rate, low power, and low radio transmission ranges that are typical in WSNs. This paper proposes a modification to the IEEE 802.15.4 standard that achieves efficient power savings for the sensor nodes, better channel utilization, and improved reliability. The proposal is based on the addition of a sleeping state that allows nodes to save more power while reducing the level of packet collisions. The sleeping periods can be tuned such that the highest level of channel utilization is achieved. A theoretical analysis based on Markov chain is performed to derive a mathematical model for our proposal. Using Matlab software, we show that we can achieve high levels of channel utilization, enhance reliability, and save more power compared to the performance of the original IEEE 802.15.4 standard.

Plug-in electric vehicles (PEVs) will not only have a substantial influence on the emerging smart grid system but also create numerous challenges for the utility and customer to deal with their connections and charging. Authentication and authorization processes are critical elements to enable mass deployment of charging stations and to provide authorized customers to access the charging facility. Works on authentication system for PEV charging infrastructure are limited, and are mainly based on centralized architectures. In this paper, we propose a comprehensive decentralized authentication mechanism for PEV charging infrastructure in order to overcome shortcomings of the centralized authentication system and to provide robust authentication in multi-server environment. We present system analysis including analysis of security and functional requirements. Compared to the prevailing centralized scheme, the proposed system reduces authentication latency and is more efficient and robust.

New services and applications that employ the advances in the Information and Communication Technologies (ICT) to the electrical power grid are rapidly emerging and consequently the traditional power grid is evolving into a smart grid. In the smart grid, communication among the supplier controlled generation units, utility administered transmission and distribution system and the consumer devices is providing new opportunities for improving the resilience and the efficiency of the grid. Resilience is a significant issue due to increasing demand, and in contrast, diminishing fossil fuels. Moreover, in the near future, resilience is expected to become a more significant concern especially due to the additional loads of the Plug-In Hybrid Electrical Vehicles (PHEVs). PHEVs are expected be widely adopted as passenger cars and as commercial vehicle fleets since they have low carbon emissions and low operating costs. On the other hand, their load on the power grid should be managed so that they do not cause failures. In this paper, we propose the Communication-based PHEV Load Management (Co-PLaM) scheme to control the load of the PHEVs. In our scheme, utilities provision a certain amount of energy for each distribution system based on the predicted supply level. The provisioned energy is communicated to the Substation Control Center (SCC) where each charging request is either accepted or rejected based on the utility set limits. Then, these decisions are sent to the smart charging stations through a Wireless Mesh Network (WMN) that uses IEEE 802.11s. In this paper, we simulate the Co-PLaM scheme and also mathematically analyze the blocking probability of the system. We show the performance of WMN in terms of delivery ratio, delay and jitter. Furthermore, we provide the blocking results and show the required additional capacity to supply all the PHEV loads without causing grid failures.

Secure Border Gateway Protocol (S-BGP) mandates that upon reception of a BGP UPDATE message, an S-BGP speaker must verify nested signatures of all nodes in the traversed path; and the router should verify the Address Attestation to check if the source has the right to announce the address prefix. Due to several digital signatures required in each UPDATE, there is a high CPU overhead associated with S-BGP. In this paper, we propose a new approach that reduces the burden of validating the AS-path and the address prefix origination. We define a control layer of trusted nodes that is comprised of major Autonomous Systems (ASes) in the network. In this environment, an AS has to verify only the signatures of intermediate ASes between itself and the last trusted node in the AS-path. Similarly, the address prefix is validated only if it was not previously validated by a trusted AS. Using an original analytical model as well as a simulation model, we measured performance metrics of the new proposal. We show that even with small ratio of trusted nodes, the new scheme can significantly reduce the number of verifications required to validate the AS-path and IP prefixes and the number of public keys required by S-BGP.

Passive Optical Network (PON) deployments have recently been aiming to combine the capacity of metro and access networks in the last mile of the Internet service provisioning. Deployment of PONs by running fiber to the premises introduces the advantage of huge capacity but at the same time, it calls for a robust design in order to avoid long service outage durations in case of network failures where survivable network design is mostly limited to the deployment budget. In this paper, we propose three mixed integer linear programming (MILP) models for various survivability policies to deploy reliable long-reach PONs under the budget limitations. Each MILP model aims to place the ONUs in optimal locations so that the covered area is maximized while availability requirements of the users are satisfied within the deployment budget. We solve the MILP models under the uniform and heterogeneous availability requirement scenarios and show that service availability and coverage introduce a trade-off so as the coverage and deployment cost do. Two out of the three survivability policies can guarantee 99.99% service availability while the third one is able to guarantee 99.999% by running the proposed MILP models. However, the first two schemes are able to cover larger area when compared to the third scheme which is the most reliable protection policy.

In this paper, we have proposed a dynamic IP address assignment architecture for wireless heterogeneous sensor networks. The assignment scheme and the architecture guarantee that communication channels can be assigned only between the registered devices ensuring the security. The dynamic IP address assignment scheme is based on the advertisement of the IP address utilization status at the base stations. Thus, each base station advertises its IP address utilization database when the ratio of the negative acknowledgement messages received from the DNS exceeds a certain threshold. By simulations, we have shown that the proposed assignment scheme introduces significant enhancement in terms of blocking probability when compared to an approach where each base station has its own IP address pool. Furthermore, we have defined three types of blocking, the real blocking, the unjustified acceptance and the unjustified rejections. We have seen that the proposed scheme can lead to lower blocking probability compared to the uniform IP assignment as long as the update threshold is kept below 1.5%.

In a peer-to-peer database management system(P2PDBMS) system, peers exchange data in a pair-wise fashion on-the-fly in response to a query without any centralized control. Generally, peers create a temporary session during data exchange. The data might be trapped and disclosed by the intruders while exchanged over an insecure communication network. As there is no centralized control for data exchange among peers, we cannot assume any central third party security infrastructure (e.g. PKI) to protect confidential data of an eHealth P2PDBMS. So far, there is currently no available/existing security protocol for secured data exchange in eHealth P2PDBMS. In this paper we propose a security protocol for data exchange in eHealth P2PDBMSs based on pairing-based cryptography and data exchange policy. The proposed protocol allows the peers to compute their secret session keys dynamically by computing pairing on elliptic curve based on the policies between them during data exchange. Our proposed protocol is robust against the man-in-the middle attack, the masquerade attack and the replay attack.

Rate adaptation has become one of the basic techniques in enhancing the capacity in todays multihop 802.11 WLANs. It is designed to cope with the status of wireless channels and achieve higher system spectral efficiency by exploiting the multi-rate capability provided by the IEEE 802.11 physical layer (PHY). As such, one of key aspects in designing rate adaptation scheme is the prior knowledge of the channel state. This becomes challenging when considering a fading channel conditions, where time varying channel gains cause random frame losses that need to be distinguished from those due to collisions and strong interference. In this paper, a new rate adaptation scheme that adopts a Kalman filter to predict the channel conditions is proposed. By predicting the future signal-to-interference noise ratio (SINR), the losses due to poor received signal and that of strong interference are taken into consideration. Furthermore, and to ensure correct operation of Kalman filter, the application of fuzzy logic controller has been explored for online tuning of Kalman Filter parameters. By tracking the covariance value of the measured interference instants, Qt, the convergence of the Kalman filter can be observed and corrective measures using fuzzy logic can be applied to prevent divergence. The soundness of the proposed rate adaptation scheme is demonstrated by comparing with existing approaches through discrete event simulation environment.

Information and Communication Technologies (ICT) are playing a key role in converting the traditional power grid into a smart power grid, and hence, they provide a number of opportunities to develop novel applications for the new cyber-physical power infrastructure. Interconnection of the smart appliances, consumer devices, Plug-In Hybrid Electric Vehicles (PHEV) and local renewable energy generation resources with the smart grid enables energy and demand management for the cyber-physical power infrastructure. In this paper, we employ a Home Gateway and Controller (HGC) device that communicates with the PHEV and controls its charging and discharging profile. HGC can also communicate with the controller of the solar power generation unit in the smart home, and it can schedule the consumption of the smart appliances accordingly. Moreover, since PHEVs draw large amount of electricity, simultaneous charging in a neighborhood can overload the utility transformers in the distribution substations and risk the resilience of the power grid. To avoid this, HGC communicates with the other HGC devices in the neighborhood and coordinates PHEV loads. Our simulation results show that, efficiency of a PHEV as a storage unit increases as it is plugged for longer periods. Moreover, when renewable energy resources are not available, a larger portion of the PHEV battery can be used for storing energy during off-peak hours, and discharging during peak hours to accommodate the household demand. Thus, we show that HGC is able to provide savings for the consumers and it can also coordinate the power supply such that the availability of solar power increases the efficiency and reduces the utilization of PHEV battery.

Smart grid aims to empower the current power grid with the capability of supporting two-way energy and information flow; and facilitating the integration of advanced computer technology and renewable energy sources into the grid. We assume a smart home with a wireless sensor network based on Zigbee. The smart home contains elements like light or temperature sensors at every room, HVAC (heating, ventilation, and air conditioning), smart appliances, thermostat and smart meter. Furthermore, there is a central computer that can communicate with all these elements. Web service is implemented on central computer and it can be accessed over the internet. The paper proposes an approach that makes use of the web services technologies to remotely interact with smart home elements in a smart grid environment. These interactions include adjusting the temperature according to personal preference or reading energy consumption. Furthermore, utility provider can interact with the smart home via web services and can facilitate demand response or selling energy back to the grid. Some scenarios are shown to describe the interactions in more detail. The performance, advantage and limitations of the radio communications between user (e.g., utility provider) and elements via web services are demonstrated in this paper.

In an eHealth peer-to-peer database management system(P2PDBMS), peers exchange data in a pair-wise fashion on-the-fly in response to a query without any centralized control. Generally, the communication link between two peers is insecure and peers create a temporary session while exchanging data. When peers exchange highly confidential data in an eHealth network over an insecure communication link, the data might be tampered with or trapped and disclosed by intruders, which is a serious offence for the clients of an eHealth P2PDBMS. As there is no centralized control for data exchange in eHealth P2PDBMS, it is infeasible to assume a centralized third party security infrastructure to protect confidential data. So far, there is currently no available/existing security protocol for secured data exchange in eHealth P2PDBMS. In this paper we propose three models for secure data exchange in eHealth P2PDBMSs and the corresponding security protocols. The proposed protocol allows the peers to compute their secret session keys dynamically during data exchange based on the policies between them. Our proposed protocol is robust against the man-in-the middle attack, the masquerade attack, and the replay attack.

Fingerprinting is chosen as the localization approach as fingerprinting has a higher accuracy than other approaches such as time-of-arrival or angel-of arrival. This paper introduces a positioning system based on IEEE802.15.4/ZigBee-based sensor networks. The system uses fingerprinting and employs Support Vector Machines (SVMs) to estimate node position. The system is cost-effective since it works with real deployed IEEE 802.15.4/ZigBee sensors nodes. The whole system requires minimal setup time, which makes it readily available for real-world applications.

In multihop, multi-rate wireless networks, simultaneous transmissions can interfere with one another to impair the transmission quality and prevent correct frame reception. Achieving high network performance (e.g. throughout and energy consumption) in such networks therefore requires a balance between the spectrum spatial reuse and the transmission quality. To achieve this trade-off, a decentralised control algorithm is proposed that allows a sender–receiver pair, using the IEEE 802.11 four-way access method, to dynamically adjust the transmit power and rate for their frames according to the level of interference in the network. Specifically, the scheme is based on the interplay between two approaches: physical carrier sensing and virtual carrier sensing approach to achieve this optimal trade-off. The algorithm outlines the rules for performing power and rate assignment so that higher performance is obtained. A realistic analytical model is presented to study the performance of the proposed heuristic; analytical results show that the algorithm proposed by the authors, indeed, finds the balance between spatial reuse and transmission quality through its appropriate search for the suitable transmission parameters. Simulation results for different topologies are used to demonstrate the significant throughput and energy gains that can be obtained by the proposed scheme.

Wireless network technologies are undergoing rapid advancements. Researchers are currently envisioning different attractive properties of wireless systems such as the ability to self-organize, self-configure, self-heal, self-manage, and self-maintain. Different wireless networks having the potential to offer cost-effective home and enterprise access networking solutions are being researched. Concepts such as dynamic spectrum access, convergence, unified network architectures, and seamless service access in heterogeneous networks are gaining widespread popularity. Technologies such as Wireless Mesh Networks (WMNs), WiFi, WiMAX, LTE, Bluetooth, ZigBee, RFID, IEEE 802.20, IEEE 802.22, and software defined radio are becoming increasingly popular. Even though these technologies hold great promises for our future, there are several research challenges that need to be addressed. A significant portion of these research challenges are attributed to security and privacy issues in these kinds of networks. This Special Issue has been launched with the aim to publish a few high quality research papers related to the recent advances in the security and privacy of different emerging and next-generation network technologies. We have received a large number of submissions for this Special Issue. However, only a few of papers that have been adjudged to be of relatively high quality as per the results of an independent peer review process could be accepted. They are summarized below. In WLAN security policy management, the standard IP-based access control mechanisms are not sufficient due to dynamic changes in network topology and access control states. The role-based access control (RBAC) models may be appropriate to strengthen the security perimeter over the network resources. Bera et al. have proposed in this paper a WLAN (wireless local area network) security policy management framework based on a formal spatio-temporal RBAC (STRBAC) model. The present work primarily focuses on dynamic computation of security policies based on various control states, its formal representation using STRBAC model and security property verification of the proposed STRBAC model. The proposed policy management framework logically partitions the WLAN topology into various security policy zones named as Central Authentication and Role Server (CARS) and a Global Policy Server (GPS). Each policy zone consists of a policy zone controller (WPZ con) which dynamically computes the low level access configurations. Finally, a SAT based verification procedure has been presented for verifying the security properties of the proposed STRBAC model. Khurana and Gupta have presented an end-to-end algorithm. According to them this is more efficient than the existing one in spatio-temporal way. This algorithm does not require clock synchronization as it is independent of space and time. They have proved that their algorithm is able to detect wormholes with tunnel length greater than or equal to ()rmax where p = , where rmin = minimum communication range and rmax = maximum communication range. They also studied the effect of error in the positions of the node on the wormhole detection capability. With the help of simulations they have shown that detection mechanism is also possible when tunnel length is less than or equal to ()rmax. Shrisat and Bhargava have presented a local, distributed hole detection algorithm for sensor network that identifies the geographical boundary of voids in the network assuming the relative geographic information of only 2-hop neighbors. This algorithm is distributed, O (k) per node computation (for k 2-hop neighbors) and requires synchronization between nodes that are not more than 2-hops away. They have verified it for both uniform and non-uniform distributions. The algorithm takes a local best-effort approach and does not verify if the nodes indeed form a closed polygonal loop. They also discuss the security implications of the hole detection framework in the context of sensor networks. Pathan et al. have proposed a new deployment model of distributed sensor network termed as HDSN(Heterogeneous Distributed Sensor Network). Based on the novel deployment model, they have proposed a secure group association management scheme that could be employed alongside other supplementary security mechanisms for HDSN. They have also presented an efficient pair wise key derivation scheme between two sensor nodes to resist any adversary's attempt. They also discuss the characteristics of HDSN, its scopes. Aparna and Amberker have studied the numerous applications relied upon secure group communication. In some applications many users join and leave the group at the same time known as bursty behavior. They have proposed a scheme for handling all the bursty behavior scenarios and analyzing the communication and computation costs for the worst cases. They have also shown that in comparison to the scheme proposed by Wong et al., their scheme is efficient in terms of encryption and cost of generation. WLM is one of the most prevalent ubiquitous Instant Messaging application programs that dramatically changes the way of communication for human beings in the past decade in all aspects. Few researches have formally incorporated the DF of WLM into generic guidelines for the associate personnel to follow. Cheng Chu et al. have provided the system architecture of the experiment accompanied with their proposed Check Point methodology trying to disclose the possible digital evidences that could be explicitly collected and scientifically presented as probative evidences with respect to the persistently mushrooming information security incidents in the next generation wireless communication networks. As vehicular networks approach deployment phases, there is wide recognition for challenges and pressing needs for solutions with respect to the areas of security, privacy, and performance. One of the stringent requirements in this area is that of protecting the privacy of vehicle owners (i.e., their anonymity and their vehicle's location unlinkability) during their participation in a vehicular network, such as in traffic safety applications. In this paper the authors have presented novel models of concrete anonymity and unlinkability requirements for vehicular networks. One key aspect of their modeling consists of recognizing the existence and impact of additional certification authorities managed by vehicle manufacturers. The resulting vehicular-network key infrastructures satisfy desirable combinations of anonymity, unlinkability, bad actor detection, and performance. One of the main drawbacks of Slotted ALOHA is its throughput collapse at higher traffic load condition due to excessive collisions and known as stability problem. The maximum throughput of Slotted ALOHA can be achieved by the knowledge of the number of active mobile nodes and the average rate of the attacking. Jahangir and Hussein have presented in this paper a self-stabilized slotted ALOHA system against the random packet destruction attacking noise packets. Results show that the system provides nearly optimal stable throughput without the knowledge of current active number of mobile nodes and current attacking packets arrival rate. The proposed system is truly distributive in nature and can be easily implemented in wireless access systems without requiring any centralized control and can defend against random packet destruction Denial of Service (DoS) attack. We are thankful to all those authors who considered submitting their work to this Special Issue, irrespective of whether their papers could be accepted or not. We are thankful to all the Referees, who painstakingly reviewed the papers. Without their hard work and dedication, it would not have been possible to select these high quality papers within the time limits of this Special Issue. We are extremely grateful to the Editor-in-Chief, Professor Hsiao-Hwa Chen, and the Editorial Staff of this Journal for supporting the launch of this Special Issue and providing help whenever it was required.

Abstract One of the main drawbacks of Slotted ALOHA is its throughput collapse at higher traffic load condition due to excessive collisions and known as stability problem. A random packet destruction Denial of Service (DoS) attack can increase the throughput collapse by increasing the collisions further. The current security protection techniques such as encryption, authentication and authorization cannot prevent these types of attacks, since the attacking packets destroy those packets by colliding those encrypted, authenticated and authorized packets. The maximum throughput of Slotted ALOHA can be achieved by the knowledge of the number of active mobile nodes and the average rate of the attacking packet arrival rate. However, the knowledge of these two parameters' current values are difficult and sometimes impossible to know. A self‐stabilized Slotted ALOHA system against the random packet destruction attacking noise packets is presented in this paper. Results show that the system provides nearly optimal stable throughput without the knowledge of current active number of mobile nodes and current attacking packets arrival rate. The proposed system is truly distributive in nature and can be easily implemented in wireless access systems without requiring any centralized control and can defend against random packet destruction DoS attack. Copyright © 2010 John Wiley & Sons, Ltd.

A Mobile Ad-hoc NETwork (MANET) is an infrastructureless network consisting of self-configuring mobile nodes connected by wireless links. Nodes rely on each other to store and forward packets. Most of the proposed MANET protocols assume cooperative and friendly network context, and do not address security issues. Furthermore, MANETs are highly vulnerable for passive and active attacks because of their open medium, rapidly changing topology, lack of centralized monitoring. Encryption and authentication solutions, which are considered as the first line of defense, are not sufficient to protect MANETs from packet dropping attacks. Most of the current Intrusion Detection Systems (IDSs) for MANETS rely on the Watchdog technique. In this research we study the behavior of this technique and propose a novel mechanism, named: Adaptive ACKnowledgment (AACK), for solving two significant problems: the limited transmission power and receiver collision. This mechanism is an enhancement to the TWOACK scheme where its detection overhead is reduced while the detection efficiency is increased. NS2 is used to simulate and evaluate the proposed scheme and compare it against the TWOACK and Watchdog methods. The obtained results show that the new AACK scheme outperforms both of the TWOACK and Watchdog methods in terms of network packet delivery ratio and routing overhead.

In this paper, we present an efficient MAC layer scheme using Dynamic Slot Assignment (DSA) in TDMA-based MAC protocols for cluster-based wireless sensor networks. The DSA scheme is presented to analyze the energy efficiency and channel utilization in a bursty traffic environment under low traffic conditions with a large number of sensor nodes in a single cluster. The DSA scheme will allow the network to adapt to the changing traffic load. Based on the network activity, the connection is established between the cluster-head node and those sensor nodes which have data to send, and a TDMA slot is assigned to each of them dynamically. We present the complete system model and model the data traffic by a correlated stochastic process (i.e. Markov chain) for a network where the second and subsequent connection arrival rate is dependent on the first arrival rate. We numerically compare our DSA with a traditionally proposed static TDMA model, the BMA model, and a variant of the BMA model (EA-TDMA), and prove substantial improvement in the energy consumption and channel utilization in low activity sensor networks. Results show that the efficiency of the MAC protocol can be increased significantly using the presented model.

BGP is built under the assumption that Autonomous Systems (ASes) are trusted and operate according to the standard. This was quickly revealed to be untrue in the current model of the Internet. Many subsequent protocols were proposed to address the security issues of the BGP protocol. Among them, SBGP offer secure and guaranteed means to distribute route reachability information. However, the assumption under which the protocol is built resulted in a significant computational overhead due to extensive use of cryptographic operations. Indeed, upon the reception of an update, a node has to verify the embedded signature of each node in the AS-PATH in an onion fashion. In this paper, we present a novel approach that reduces the cost of construction and verifications of BGP updates. We make the assumption that some ASes (Like Tier-1 ISPs) can be considered to be trusted by the rest of the ASes. We build a new protocol that employs symmetric and asymmetric cryptosystems to build a secure and efficient mechanism to distribute route information. Based on simulation studies, we noticed considerable reduction of the cost of update construction and verification despite a slight increase of the messages exchanged to reach the steady state.

The application of Wireless Sensor Networks (WSNs) in Intelligent Transportation Systems (ITSs) has been the topic of extensive research in the last decade. Various aspects of WSNs have been addressed in the context of transportation networks. In particular, the different aspects of security (confidentiality, integrity, and availability) strongly enticed the research devoted to ITSs. However, those efforts concentrated on preventive techniques constituting a first line of defense (like cryptography and authentication), which are effective in inhibiting the diverse malicious attacks. Relatively, little attention has been paid for employing a second line of defense that can detect intrusive behavior after successfully penetrating the first one. The latter line of defense is known as the Intrusion Detection System (IDS). While mature in wired and many types of wireless networks, IDSs are envisaged to have more opportunities in WSNs. In this paper, we study the incorporation of IDSs in WSN-based ITSs. We distinguish the characteristics of ITSs that affect the design of effective security measures and propose a novel IDS based on the WITS architecture (proposed in [1]).

We study the benefits and trade-off of using scheduled lightpaths for traffic adaption. We propose a network planning model, which allows lightpaths to slide within its desired timing window with no penalty on the optimization objective, and to slide beyond its desired timing window with a decreasing tolerance level. Our model quantitatively measures the timing satisfaction or violation. We apply the Lagrangian Relaxation and Subgradient Method to the formulated optimization problem. Our method demonstrated great computational efficiency when compared with other existing algorithms. Our simulation results show how timing flexibility improves network resource utilization and reduces rejections.

Using discrete-time Markov chains to analyze the performance of contention-based medium access control (MAC) protocols has been a common practice since its initial proposal by Bianchi in his seminal paper published in 2000. The way these methods work is by modeling each individual node competing for the medium in a wireless network as a Markov chain. Performance metrics of the whole system, such as throughput, delays and losses, can then be obtained from the model. However, these methods implicitly assume that Markov chains modeling individual nodes are independent from each other, which is not necessarily true in most situations. In this work we propose a more realistic model in which the whole network with all of its nodes is modeled using a single Markov chain, and in which assuming independence is no longer necessary. We reduce the complexity of the problem, both in processing and memory requirements, by taking advantage of its inherent symmetry, which allows us to work with only a few selected representative states. We evaluate how results from both types of methods compare to each other and to simulations. Our findings show that the old method has a very poor performance as compared to the new one.

We present a novel analytical framework to investigate the performance of activity based TDMA slot scheduling under varying traffic conditions in cluster-based wireless sensor networks. Dynamic TDMA Slot Scheduling (DTSS) scheme is presented to analyze the channel utilization and packet dropping probability in bursty network environment under low and high traffic conditions with a large number of sensor nodes in a single cluster. DTSS scheme will allow the network to adapt to the changing traffic load. Based on the network activity, the connection is established between the cluster-head node and those sensors nodes which have data to send, and requested number of TDMA slots is assigned to them dynamically. We have modeled the data traffic by a correlated stochastic process (i.e. Markov chain) for a network where the second and subsequent connection arrival rate is dependent on the first arrival rate. We numerically compared DTSS with traditionally proposed static TDMA model and proved substantial improvement in the bandwidth efficiency and decrease in connection blocking probability in low activity networks. The drawback of the proposed system is also investigated. Results show that the efficiency of the MAC protocol can be increased significantly using the proposed model with reasonably low packet dropping probability.

This paper explores the benefits of incorporating the demand-bifurcation feature into the design and planning process of the multi-granular optical network under the fiber-scarce situation. Our simulation results demonstrate that the bifurcation of demands at all traffic granularity levels can only be beneficial provided that the traffic pattern is uniform and both the traffic intensity and network physical connectivity are high.

A random packet destruction Denial of Service (DoS) attacking signals are easy to mount and difficult to detect and prevent. The attacker does not need to pretend a legal user and able to shut down any Slotted ALOHA based wireless Ad Hoc and sensor networks successfully by reducing the throughput and stability. Since current anti-attack measures such as encryption, authentication and authorization cannot prevent these types of attacks, we propose the use of multiple power levels transmission system to mitigate the attacking signals. Through analysis and numerical examples we demonstrate that the multiple power levels transmission system can significantly improve the throughput and stability of Slotted ALOHA under the random packet destruction Denial of Service (DoS) attacking signals. The implementation of the multiple power levels transmission system is easy and can keep the system running, although current anti-attack measures such as encryption, authentication and authorization cannot prevent these types of attacks.

A multimedia surveillance system aims to provide security and safety of people in a monitored space. However, due to the nature of surveillance, privacy-sensitive information, such as face, gait and other physical parameters based on the captured media from multiple sensors, can be revealed without the concern of the people. This is a major concern in recent days. Therefore, it is desirable to have such mechanism that can hide privacy-sensitive information as much as possible, yet supporting effective surveillance tasks. In this paper, we propose a chaos cryptography based data hiding approach that can be applied on selected regions of interest (ROIs) in video camera footage, which contains privacy-sensitive data. Our approach also supports multiple levels of abstraction of data hiding depending on the role of the authorized user. In order to evaluate the suitability of this approach, we applied our algorithm on some video camera footage and observed that our approach is computationally efficient and applicable for real-time video surveillance tasks.

The nature of a time variant channel environment have posed significant challenges on the design of new communication protocols and applications for IEEE 802.11 based multihop networks. The ability to predict the channel status enables these networks to better exploit the network resources and take precautionary measures, when necessary, to improve the channel reuse through tuning protocol parameters (such as transmit power, carrier sensing threshold and transmission data rate). This work suggests the use of Interacting Multiple Model (IMM) estimator, which is build from a (K) number of Kalman Filters to work in parallel, in order to predict the future signal-to-interference in a wireless network with time-varying channel conditions. These predictions are then used by a rate adaptation scheme in discrete event simulation environment to ensure proper and predictable resource usage.

In this paper, a random access protocol for quality of service (QoS) support targeted for medical wireless body area sensor networks (WBASNs) is proposed. In this proposal, the sensor nodes are classified into nodes of life-critical health information, and nodes of non-critical health information. The proposed QoS-based MAC protocol prioritizes the critical packets access to the transmission medium by cutting of the number of retransmissions of the collided non critical packets. Therefore, the critical traffic throughput is increased and its rejection rate is decreased while maintaining the non critical traffic QoS parameters above a minimum provisioned level. The proposed protocol is evaluated analytically and through simulation. The obtained results demonstrate a dramatic increase in the critical traffic throughput.

Smart grids aim to integrate recent advances in communications and information technologies to renovate the existing power grid. In smart grids, consumers can generate energy and sell it to the utilities. Moreover, they can avoid consumption during peak hours which helps reducing the peak load on the grid. Energy-aware homes can aid consumers to manage their demand and supply profile. In this paper, we propose Appliance Coordination with Feed In (ACORD-FI) scheme for such energy-aware smart homes. We show that ACORD-FI decreases the cost of energy consumption of home appliances, significantly.

This paper presents a comparative study between the dynamic survivability approaches in WDM mesh networks. The paper focuses on the diverse routing and the p-cycle approaches to protect mesh networks against single span failure under dynamic traffic. The computational complexity and the blocking performances of both approaches are analyzed and compared. Simulation results suggest that the p-cycle approach has better blocking performance than the diverse routing approach. Additionally, the lower computational complexity of the p-cycle approach algorithm makes it more suitable, especially at highly dynamic traffic. As a result, the p-cycle approach scales better with the network size and the dynamic nature of the traffic than the diverse routing approach. Therefore, the p-cycle approach has presented itself as a better option than the diverse routing to solve the survivability problem in dynamic WDM wavelength-routed networks. Other advantages of the p-cycle approach include their fairness to requests with long routes.

In this paper, we propose a bandwidth allocation scheme working with differentiated services for the Multi-Point Control Protocol (MPCP) in Long-Reach Passive Optical Networks. The proposed scheme is an enhancement to our recently proposed bandwidth allocation scheme Periodic Gate Optimization (PGO), and it is called Periodic Gate Optimization with Quality of Service Awareness (PGO-QoS). Long-Reach PON introduces a challenge by the deployment of passive elements in a long distance up to 100km between the OLT and the ONUs. It becomes more challenging when the subscribers have different Service Level Agreements (SLAs) with specific performance requirements such as delay bounds and/or packet drop probabilities. PGO-QoS consists of two independent modules; intra-ONU scheduling and dynamic bandwidth allocation. Intra-ONU scheduling stands for the burstification of the buffered packets at the ONUs, and it determines the proportion of the packets to be dequeued from the buffer of each SLA class. These proportions are also appended to the REPORT message to be used by the OLT in the dynamic bandwidth allocation module. The bandwidth allocation module runs at the OLT. This module is mostly inherited from recently proposed PGO. Based on the collected REPORT messages, the OLT periodically builds an ILP model to estimate the appropriate GATE credits of the overloaded ONUs until the next optimization period. The ILP model sets the appropriate constraints so that the OLT tends to prioritize the ONUs where dequeuing proportions of the high priority queues are greater. The simulation results show that PGO-QoS leads to a lower average delay and shorter queue length and less packet delay. Moreover, the proposed scheme also introduces decreased delay and low packet loss for the higher priority SLA classes which are class-3 and class-2.

The trend in the development of intelligent optical networks is the move towards a unified solution, to support voice, data, and various services. Nowadays, different applications may need different levels of protection and differ in how much they are willing to pay for the service they get. A control scheme which is used to set up and tear down lightpaths, should not only be fast and efficient, but also be scalable. In addition, it should also try to minimize the connection cost and the number of blocked connections while satisfying the requested level of availability. In this work we choose the availability of a connection as a quality of service (QoS) parameter to denote different levels of protection. It is proven that the Availability-Guaranteed least-cost (AGLC) routing problem is NP-complete. We propose a distributed control scheme based on parallel fixed alternative routing approach for establishing AGLC lightpaths. The proposed framework performance is studied through extensive simulation experiments on wavelength selective network with different traffic loads. The simulation results show that our proposed framework provides better performance in terms of average blocking probability, and average routing distance average path cost.

In this paper, a Cognitive Radio based Medium Access Control (CR-MAC) protocol for Wireless Body Area Sensor Networks (WBASN) that utilizes cognitive radio transmission is proposed. In this proposal, the sensor nodes are classified into nodes of life-critical health information, and nodes of non-critical health information. The CR-MAC protocol prioritizes the critical packets access to the transmission medium by transmitting them with higher power while transmitting lower priority packets using lower transmission power. At the receiver, a higher priority packet experience collision only when there are more than one critical packet transmission at the same time slot while non critical packets experience collision when there are more than one transmission at the same time slot. This protocol is evaluated analytically. The obtained results demonstrate a differentiated service system which prioritizes critical traffic access to the transmission medium and increases the critical traffic throughput.

Coexistence of Plug-in Hybrid Vehicles (PHEVs) with the emerging smart grids has been recently an attractive and equally challenging research topic. The existing electricity grids are rapidly evolving into smart grids by utilizing the advances in Information and Communication Technologies (ICT). Meanwhile, advances in Lithium-Ion (Li-ion) battery technologies have made manufacturing of PHEVs cost-wise effective, and PHEVs are expected to be widely adopted in the following years. PHEVs have several benefits over conventional vehicles such as, less fuel dependency, lower operating costs and lower amount of CO2emissions. On the other hand, unless PHEVs are powered by off the grid renewable energy resources, they will be drawing electricity from the grid to charge their batteries and they will increase the load on the grid. In the worst case, when the Time Of Charging (TOC) coincides with the critical peak periods, the grid may experience overall or partial failure. For most of the cases, TOC may be during the peak hours when the price of electricity is high. To avoid endangering grid resilience and to avoid high costs, a charging strategy and communication with the smart grid is essential. In this paper, we propose a prediction-based charging scheme which receives dynamic pricing information by wireless communications, predicts the market prices during the charging period and determines an appropriate TOC with low cost. Our prediction-based charging scheme is based-on a simple, light-weight classification technique which is suitable for implementation on a vehicle or a charging station. We show that prediction-based charging provides less operating cost and less CO2emissions.

In this paper, we propose a planning heuristic called Locate-ONU-with-Lowest-Availability-Requirement-First (LOWLARF) to compare the coverage capability of three previously proposed survivability policies under these constraints. The heuristic is designed to determine the length of the feeder fiber and to locate each ONU on the appropriate location in order to meet the availability requirements while not violating the budget limit. The heuristic is shown to locate the ONUs within the availability requirements and the budget limit. In the test scenarios, ONUs are assumed to contract the users requesting different availability levels while a pre-specified budget limit is set for each scenario. By our proposed planning heuristic, we compare three survivability schemes under various budget constraints and split ratios within various square regions. We show that the better the availability the less the coverage in terms of total deployed fiber length. Furthermore, we also show that better protection leads to a smaller ONU region while less protection allows to cover a larger region by the ONUs.

Since several years, communications between fixed and mobile units have been studied in areas in underground tunnels. The leaky feeder (LF) is one of the most useful results of these studies. The LF technology in combination with other communication systems allows us to reduce the transmission power of the mobile entities without sacrificing quality of service. Because the leaky feeder cables are able to transfer both power and RF signal; these technologies are considered as particular case of line power communication. In this paper we present and analyze the results of narrowband and wideband radio channel characterization. The measured frequency bands are selected for uses in several applications (WPAN, CDMA, video and analog telephony). The measurement were performed in underground mine gallery.

The electricity grid is undergoing a major renovation and becoming a smart grid by integrating the advances in Information and Communication Technologies (ICT). Current applications in energy generation, power distribution and its consumption need improvement in several ways, such as, making efficient use of green energy, increasing automation in distribution and enabling residential energy management. The existing grid does not provide sufficient mechanisms to manage the residential electricity consumption. However, interconnecting consumer devices with the home area networks, and at the same time, communicating with the utility networks through a home gateway facilitate residential energy management in smart grids. Residential energy management uses utility-driven price signals which vary depending on the time of the day. This is called as Time Of Use (TOU) pricing. In TOU pricing, electricity consumption during peak hours costs more than electricity consumption during off-peak hours. TOU prices reflect the variation in the actual cost of power during one day. Utilities run bas plants to supply power for the base load. In peak hours, demands of the consumers rise, and utilities bring peaker plants online to supply additional power. Peaker plants have higher operating costs and higher GreenHouse Gas (GHG) emission rates than base plants. Therefore, reducing peak load decreases the expenses for energy generation and it decreases the GHG emissions. Wireless sensor networks can play a key role in reducing the demand of the consumers in peak hours. In this paper, we employ TOU-aware energy management in a smart home with wireless sensor home area network and analyze the impact of this schemes on the peak load. We show that our scheme decreases the use of the appliances in peak hours and reduces the energy bills for consumers.

Wireless Sensor networks (WSN) have become a focus of research in the last few years. WSN is composed of small battery-powered devices that has sensors and wireless communication capabilities. Energy management is one of the key issues in WSNs because it directly impacts the network life-time. In order to overcome this restriction, several energy-efficient approaches for different layers have been investigated. In this paper, energy optimization on physical layer is analyzed. The node's power consumption is optimized through scaling the modulation scheme used in node communications. Results show that an optimal modulation scheme can lead to the minimum power consumption over the whole wireless sensor network.

In cluster-based two-tier Wireless Sensor Networks (WSNs), the cluster-head nodes (CHs) gather data from sensors and then transmit to the base station. When these cluster head nodes start to die, the coverage of the respective clusters is lost and it leaves the region unmonitored. Even if the CHs are rotated and reassigned after some time, until the next rotation that cluster in question will be out of cluster head, causing a loss of information and loss of coverage. To select a Backup Cluster Head (BCH) is suggested for those CHs which are close to deplete their energy [1]. When the CH dies, BCH takes over the responsibility and continues to work as a new cluster head. In this paper we present an analytical model of cluster reliability in cluster-based WSN using BCH, based on Markov chain model. We use non-homogeneous Markov process, along with Forward Chapman-Kolmogorov equations to illustrate the cluster monitoring period in a finite three state space model. We test the accuracy of the model by applying the probabilities of failure of CH and BCH nodes, for a fixed number of sensor nodes in a cluster. The results show that the presented model is able to match the behaviour of the cluster state transition accurately and validates the simulation results and analysis published in [1].

Wireless sensor networks (WSNs) are considered due to the ubiquitous nature, ease of deployment, and wide range of possible applications. WSNs can be deployed in unattended environments, where a registered user can login to the network and access data collected by the linked sensors. Authenticating users in resource constrained environments is one of the major security concerns. Since sensor nodes have limited resources and computation power, it is desirable that the authentication protocol is simple and efficient. In 2009, M. L. Das proposed a two-factor authentication for WSNs, where a user has to prove possession of both, a password and a smart card. Since his scheme utilizes only cryptographic one-way hash function and exclusive-OR operation, it is well-suited for resource constrained environments. However, Khan and Algahathbar pointed out that Das's scheme has some flaws and is vulnerable to various attacks and proposed an alternative solution. In this paper, we show that both, Das's and Khan-Algahathbar's schemes have flaws and remain vulnerable to various attacks including stolen smart card attacks. To overcome the security weaknesses of both schemes, we propose an improved two-factor user authentication that is resilient to stolen smart card attacks as well as other common types of attacks. We provide security evaluation of the proposed protocols showing its robustness to various attacks and analyzed the scheme's performance to determine its efficiency. Compared to the previous schemes, it is proven more robust and provides better security.

Privacy and security are two important issues in vehicular networks. Users wish to maintain location privacy and anonymity, meaning the identity, location/direction of move of their vehicles remains unknown to everybody with possible exception law enforcement authorities responsible by law to know and maintain such private information. In this paper, we propose a Pre-broadcast based Time Efficient Privacy (PTEP) scheme, which, instead of performing any asymmetric verification, uses Message Authentication Code (MAC) functionality and HASH operations to authenticate messages. Moreover, we use two-level key (upper-level hash chain and low-level hash chain) which assists avoiding message losses. Analysis shows that the proposed PTEP scheme superior performance in terms of packet loss rate and packet latency. In addition, it can be used to serve emergency and routine messages as well, while most of existing solutions can only work with routine messages.

Abstract In this paper, a Cognitive Radio Based Medium Access Control (CR‐MAC) protocol for Wireless Sensor Body Area Networks (WSBAN) that utilizes cognitive radio transmission is proposed. In this proposal, the sensor nodes are classified into nodes of life‐critical health information and nodes of non‐critical health information. The CR‐MAC protocol prioritizes the critical packets access to the transmission medium by transmitting them with higher power while transmitting lower priority packets using lower transmission power. At the receiver, a higher priority packet experiences collision only when there are more than one critical packet transmission at the same transmission slot while non critical packets experience collision when there are more than one transmission at the same transmission slot. This protocol is evaluated analytically and through simulation. The obtained results demonstrate a differentiated service system which prioritizes critical traffic access to the transmission medium and increases the critical traffic throughput. Copyright © 2010 John Wiley & Sons, Ltd.

Intuitively, many wireless and sensing applications benefit from knowledge of network boundaries. Many virtual coordinate constructions rely on the furthest set of nodes as beacons. Network edges may also bound routing holes in the network, regions of failure due to environmental effects, or indicate the need for additional deployment. In this paper we propose an algorithm to identify nodes and links that sit on the boundaries of the physical network. Edge nodes may then participate to map the network boundaries. Our algorithm is provably correct and exploits the relationship between alphahulls, a generalisation of the convex hull, and communication range. This relationship allows nodes on network boundaries to identify themselves without outside intervention. We then show via simulation that our algorithm identifies meaningful boundaries even in networks of low-density and non-uniform distribution.

As the wireless sensor network (WSN) technology evolves towards higher transmission rates, it makes sense to start considering sensing and transmission of real-time information, such as audio and video. These applications require quality of service (QoS) guarantees, not offered by current networks. The multi-hop nature of WSN makes QoS a challenging task. In addition, researchers have recently realized that cross-layer protocols achieve a far better performance than protocol layers working in isolation. These two ingredients are the focus of our work. In this paper we propose an architecture in which the MAC and routing protocols collaborate to discover and reserve routes, to organize nodes into clusters and to schedule the access to the transmission medium in a coordinated time-shared fashion. As a consequence, not only QoS is achieved but also great energy savings by eliminating collisions and considerably reducing idle listening. The resulting protocol is called QUATTRO: QUAlity-of-service-capable clusTer-based Timeshared ROuting-assisted MAC protocol. We evaluate our proposal using simulations by examining multiple scenarios in which different numbers and densities of nodes are considered. Our results show that the protocol overhead is reasonable.

In Ad Hoc or sensor networks, communication may be achieved between mobile nodes without a central entity (base station), in a half-duplex manner. The impact of jamming signals on those kinds of networks is studied. The contributions of this paper can be divided into two parts. In the first part, the probability of success, throughput and the maximum throughput are derived for the half-duplex Slotted ALOHA in terms of the node transmitting probability, the node receiving probability and average jamming signals rate. Results show that the probability of success, throughput and maximum throughput decrease with the increase of average jamming signals rate. In the second part, the effect of jamming signals on the maximum throughput of retransmission cut-off half-duplex Slotted ALOHA is studied. A close form equation is obtained for the transmission probability from each mobile node that maximizes the channel throughput in the presence of jamming signals. This equation provides the relationship between the new packet transmission probability from each mobile node, jamming signals rate and the number of retransmission attempts. The number of retransmission attempts plays an important role for a lower value of jamming signals rate. The results of this study may be used for system design of half-duplex contention-based multiple access schemes with and without jamming signals and retransmission cut-off.

Efficient and reliable communications is a critical issue in wireless networks with lossy links. In this paper, we propose a neighbor-assisted coding aware opportunistic retransmission mechanism to increase the network throughput. The key idea behind our design is as follows. If a node fails to receive a packet due to link loss, its neighboring node(s) receiving the packet can assist the retransmission of the packet, possibly encoded with other packet(s) via localized network coding, if such retransmission is expected to be beneficial. This can effectively reduce the total number of packet retransmissions at the MAC layer. Simulation results show that our proposed mechanism can significantly increase the network throughput as compared with existing work.

The FCC has set apart a frequency band with the specific goal of improving safety and efficiency of the transportation system. Its purpose is to provide wireless communications between stations on the roadside and mobile radio units located on board of vehicles. The resulting technology is known as WAVE and is currently under development as draft standard IEEE 802.1 lp. The most time- critical messages, carrying urgent safety-related information, are transmitted over the so-called control channel (CCH). WAVE devices use the EDCA MAC protocol, defined in the 2007 version of the IEEE 802.11 standard, to compete for the transmission medium. This work analyzes the performance of EDCA under the specific conditions of the CCH of a WAVE environment. The protocol is modeled using Markov chains and results related to throughput, frame-error rate, buffer occupancy and delay are obtained under different traffic-load conditions.

We propose and analyse a new random access protocol with multiple power levels selection schemes for infrastructureless wireless networks. In these networks, mobile nodes may communicate with each other without a central entity (base station), where each mobile node will be either in a transmitting mode or in a receiving mode or in an idle mode. Throughput with random power levels selection scheme is derived in terms of the transmission probability of each mobile node, receiving probability of each mobile node and the number of power levels. Throughput with optimum power levels selection scheme is also derived and compared with the previous one. Results show that the optimum transmission probability of each mobile node to achieve the maximum throughput depends only on the number of power levels. The maximum throughput region is devised in terms of transmission probability of each mobile node and the number of power levels. The proposed new random access protocol is truly distributive in nature and can be easily implemented in infrastructure-less wireless access systems without requiring any centralized control.

In this paper, we design a destination-driven on-demand multicast routing protocol for wireless ad hoc networks. The design objective is to improve the multicast forwarding efficiency. To achieve this goal, the path to reach a multicast destination is biased towards those paths passing through another multicast destination. If multiple such choices are available, the one leading to the least extra cost is selected. Our protocol embeds this destination-driven feature into the on-demand multicast structure building process of an existing multicast protocol ODMRP. Detailed protocol design descriptions are provided. Simulation results show that our protocol can greatly improve the forwarding efficiency as compared with ODMRP. Moreover, our destination-driven design can also work well with other existing multicast routing protocols for wireless ad hoc networks.

We introduce Cooperative Fast Protection (CFP) as a novel protection scheme in WDM networks. CFP achieves capacity-efficient fast protection with the features of node-autonomy and failure-independency. It differs from p-cycle by reusing the released working capacity of the disrupted lightpaths (i.e. stubs) in a cooperative manner. This is achieved by allowing all the failure-aware nodes to switch the traffic, such that the disrupted lightpaths can be protected even if the end nodes of the failed link are not on the protecting cycles. CFP also differs from FIPP p-cycle by not requiring the source node of the disrupted lightpath on the protecting cycle. By jointly optimizing both working and spare capacity placement, we formulate an ILP for CFP design. Numerical results show that CFP significantly outperforms p-cycle by achieving faster protection with much higher capacity efficiency.

The ever increase in the Internet traffic resulted in an increase in the number of wavelengths per fibre in WDM networks. Consequently, the required number of optical ports increases which accordingly increases the cost of the optical cross connect and the complexity of the routing and wavelength assignment algorithms. As a result, the multi-granular switching concept was introduced to reduce the cost of the optical cross connect and simplify the complexity of its management algorithms. This paper proposes a new heuristic algorithm, based on the Multi-Granular traffic concept, to set up static multi-granular paths in optical networks. The objective of the new algorithm is to minimize the total weighted port count that is required to set up a given set of static multi-granular traffic demands on a given network. The new algorithm is tested and its performance is compared with other previously proposed algorithms.

One of the most debatable issues in the field of optical networks is wavelength conversion. With the introduction of the multi-granular switching concept, the debate can be extended to consider the significance of performing label conversion for all optical flows defined in Generalized Multiprotocol Label Switching (GMPLS). In order to conduct this study, we compare heuristics that are developed specifically to plan large-scale GMPLS-based transport network with and without the label-conversion capability. The simulation results show that label conversions can be quite beneficial especially when fiber resources are scarce and the network physical connectivity is high.

New applications are likely to ask for a more flexible bandwidth, large bandwidth for limited amount of time. In order to meet these new requirements, flexible optical transport networks in which connections could be set up and released on dynamic short-term basis have to be introduced. We propose a distributed Holding-Time-Aware provisioning framework based on intelligent destination routing to assign and manage the working and the protection paths as well as their wavelength(s) of each connection. In our framework, we propose to utilize knowledge of connection holding time to provide efficient provisioning of shared-path-protected connections in survivable optical mesh networks. We show through a simulation study that the performance of the proposed holding-time-aware compared to a holding-time-unaware is significant.

Implementing wireless sensor networks present new challenges compared with theoretical networks. In addition, results derived from the implementation might differ from theoretical results. Moreover, some routing protocols when implemented might fail to perform. In this paper, we implement three routing protocols namely: Dynamic MANET On-demand, Collection Tree and Dissemination Protocols using a TELOSB sensor network. Our aim is to compare their performances. To demonstrate the pros and cons of these protocols, several performance metrics are carried out. True sensors' readings are measured for future use in our simulation experiments.

The 16 articles in this special issue report cutting-edge research achievements in the field of applications of Networks for Healthcare.

Abstract In this paper, we design a localized power‐aware alternate routing (LPAR) protocol for dynamic wireless ad hoc networks. The design objective is to prolong the lifetime of wireless ad hoc networks wherein nodes can adaptively adjust their transmission power based on communication ranges. LPAR achieves this goalviatwo phases. In the first phase, energy draining balancing is achieved by identifying end‐to‐end paths with high residual energy. The second phase is designed to effectively reduce the power consumed for packet forwarding. This is achieved by iteratively performing adaptive localized power‐aware alternate rerouting to bypass each (potentially) high‐power link along the end‐to‐end path identified in the first phase. Further, the design of LPAR enables nodes to collect their neighborhood information ‘on‐demand’, which can effectively reduce the overhead for gathering such information. LPAR is suitable for both homogeneous and non‐homogeneous networks. Simulation results demonstrate that LPAR achieves improved performance in reducing protocol overhead and also in prolonging network lifetime as compared with existing work. Copyright © 2008 John Wiley & Sons, Ltd.

Fault localization is an important issue in all-optical networks. The Limited Perimeter Vector Matching (LVM) protocol is a novel fault localization protocol for localizing single-link failures in all-optical networks. In this paper, we study the fault localization optimization problem in applying the LVM protocol to static networks, where traffic (or lightpath) demand is known a priori. Given the traffic demand, the fault localization optimization problem is to optimize the traffic distribution so that the fault localization probability in terms of the number of localized links can be maximized. We formulate the problem into an integer linear programming problem and use CPLEX to solve the problem. We show through numerical results that by optimizing the traffic distribution the fault localization probability in terms of the number of localized links can be maximized. Moreover, the solution to the problem can also provide the maximum number of wavelengths needed on each link to obtain the maximum fault localization probability.

In this paper, we propose two availability-aware connection provisioning algorithms, namely global differentiated availability-aware provisioning (G-DAP) and link-by-link differentiated availability-aware provisioning (LBL-DAP) for the connections of differentiated availability classes. G-DAP attempts to provide a global feasible sharing degree for each availability class on all of the wavelengths throughout the network. LBL-DAP provides a feasible sharing degree for each class on the wavelengths of each link separately. We evaluate the performance of the proposed schemes by simulation under NSFNET topology, and compare the results with a reliable connection provisioning scheme. The connections arrive with various availability requirements. We show that G- DAP and LBL-DAP provide an enhanced blocking ratio and resource overbuild globally and for the high priority classes.

In wireless ad hoc and sensor networks, communication may be achieved without a central entity (base station) and nodes communicate with each other in a half-duplex manner. In those kinds of networks each node either will be in a transmitting mode or in a receiving mode or in an idle mode. Stability of half-duplex slotted ALOHA is studied in terms of the node transmitting probability, the node receiving probability, capture ratio and the number of retransmission attempts. A close form equation is obtained for the stable operation of a distributed random access protocol with multiple receiving nodes. This equation provides the relationship between the new packet transmission probability from each mobile node, capture ratio and the number of retransmission attempts. The results of this study may be used for system design of half-duplex contention- based multiple access schemes with and without capture and retransmission cut-off.

Network coding has been considered as an effective strategy for improving the performance of wireless mesh networks (WMNs) by encoding multiple packets into a single transmission. Existing work shows that integration of network coding and routing at the network layer can achieve good performance in terms of network throughput and packet delay. In this paper, we propose a rate-adaptive coding-aware multiple path routing mechanism for WMNs. The main design objective is to improve the network performance via traffic splitting for maximizing the coding opportunities in the network. Simulation results are used to verify the effectiveness of our proposed mechanism.

Node clustering has been widely considered in underwater sensor networks (UWSNs) to improve energy efficiency and prolong network lifetime. Network survivability is a great concern in cluster-based UWSNs. In this paper, we propose a dependable clustering protocol to provide a survivable cluster hierarchy against cluster-head failures in such networks. The proposed clustering protocol attempts to select a primary cluster head and a backup cluster head during clustering so that the cluster members associated with the failed cluster head can quickly switch over to the backup cluster head in the event of a cluster-head failure. Meanwhile, it attempts to select a set of clusters with minimum total cost so that network lifetime can be prolonged to ensure long-term underwater environmental monitoring. Simulation results show that the protocol can effectively enhance network survivability and improve network capacity in the event of cluster-head failures.

Opportunistic routing and network coding have been considered as effective strategies for improving the throughput of wireless mesh networks (WMN). However, most existing work studied opportunistic routing and network coding separately. This has largely limited the ability of the above strategies from effectively improving the network performance. To achieve improved network throughput, in this paper, we propose a coding-aware opportunistic routing mechanism for WMNs. The design goal is achieved by effectively integrating the above two strategies such that decision on each packet forwarding is made with the awareness of potential coding opportunities. Simulation results show that our proposed mechanism can remarkably improve the network throughput.

In this paper, we propose an efficient fault-prevention clustering protocol for improving the lifetime and robustness of underwater sensor networks (UWSNs). The proposed clustering protocol takes into account both the reliability and residual energy status of each sensor node during clustering, and attempts to select those healthy nodes as cluster heads through failure prediction, cost evaluation, and clustering optimization. The purpose of failure prediction is to predict the potential failure of an underwater sensor based on its lifetime distribution so that those unhealthy nodes are prevented from being selected as cluster heads. Cost evaluation is introduced to evaluate the cost caused by the failure of a cluster head. Clustering optimization aims to construct a cluster hierarchy that minimizes the overall cost of all selected clusters based on the cost evaluation of each sensor node. The simulation results show that the proposed clustering protocol can not only significantly prolong network lifetime, but also improves network robustness and capacity compared with existing clustering protocols.

Mobile devices in the IEEE 802.11 based multihop ad hoc networks support the transmission of data frames at various predefined transmission rates. To achieve high throughput performance, these multiple rates should be exploited and used in an adaptive manner depending on the channel condition. In this paper, we propose a data rate adaptation scheme with the use of Kalman Filter to determine the channel conditions (forthcoming interference). Upon receiving the RTS (request to send) packet, the receiver predicts the future interference and accordingly selects the appropriate transmission rate. Then, the receiver encapsulates the rate value in the CTS packet sent to the transmitter. Furthermore and to ensure correct convergence of the kalman Filter, we propose a fuzzy logic approach to tune the parameters of the Kalman Filter. The performance of the proposed scheme is tested and verified in a discrete event simulation environment.

To efficiently utilize the limited spectrum of interference limited Wide-band Code-Division Multiple-Access (WCDMA) cellular networks, transmission rates allocation and base station association for mobile users need to be optimal. In this paper, Power-Controlled Rate and Coverage Adaptation (PCRCA) module is proposed to balance network load, maximize number of users admitted to the system while assuring their Quality of Service (QoS) requirements. It is a cooperative scheme which allows nearby sectors of two adjacent cells to dynamically change their coverage to meet the optimal transmission rates allocation for their mobile users. A heuristic algorithm is implemented to solve an optimization model of the proposed scheme. The obtained power and capacity gains as well as outage probability of the proposed algorithm is compared to the obtained results of a system with only power-controlled rate adaptation mechanism.

In this paper, we present a new connection provisioning algorithm for availability-aware optical transport networks planning regarding shareability of backup channels. The proposed scheme is designed to work under shared backup path protection policy and attempts to minimize the conflict between unavailability per connection and resource overbuild. It is adapted into a conventional two-step availability-constrained connection provisioning scheme. We evaluate the performance of this dynamic shareability driven connection provisioning scheme in terms of unavailability per connection and resource consumption as applied to NSFNET and EON topologies. Simulation results show that dynamic shareability driven connection provisioning scheme reduces the unavailability per connection by not violating the resource consumption as much as the dedicated path protection.

In this paper, we propose a fault localization protocol for localizing single-link failures in multi-domain all-optical networks. This protocol is based on a limited-perimeter vector matching (LVM) mechanism, which restricts fault localization in a smaller perimeter area and can thus significantly reduce the time and space complexities of fault localization. By assuming power monitoring available only at edge nodes, this protocol can localize both inter-domain and intra-domain link failures without exchanging any internal confidential domain-specific information (e.g., topology and traffic information) between different domains. We show through analytical results that it can not only fast localize an inter-domain link failure between different domains but also localize an intra-domain link failure that affects inter-domain traffic faster than the open-shortest-path-first (OSPF) protocol in a large network.

In optical mesh networks, different protection schemes can be used to satisfy the service availability against network failures. However, in order to satisfy a connectionpsilas service-availability requirement in a distributed controlled WDM with dynamic traffic and no wavelength converters, we need a framework to manage the provisioning process and to select a proper protection scheme. In this paper, we propose a novel distributed Availability-Aware provisioning framework based on intelligent destination routing to assign and manage the working and the protection paths as well as their wavelength(s) of each connection. Our proposed framework probes the k most reliable paths in parallel. The probing technique used in this framework is the first probing technique that probes each path as both a candidate working path and a candidate shared protection path at the same time. Moreover, we propose to use connection availability as a metric for providing differentiated protection services in WDM mesh networks. Based on the availability information collected, our provisioning strategy selects an appropriate level of protection to each connection. The effectiveness of our provisioning approaches is demonstrated through simulation results.

Our previous work proposed a novel mechanism for coverage control in WCDMA systems that can be used in instances of congestion and load imbalance. In this paper, we expand our work to accommodate the heterogeneous nature of traffic in future networks. More importantly, we derive a mathematical model to involve more realistic considerations for inter-cell interference in a system with mixed coverage. Based on different load scenarios in a hotspot area and different coverage combinations of the loaded and supporting sectors, the model is used to quantify the degradation level in the QoS parameters of low priority traffic to preserve the QoS level of high priority traffic. Achievable data rates and Bit Error Rates (BER) are determined for every possible coverage combination. The effect of rate and coverage adaptation on the transmission powers of mobile users is also analyzed.

Orthogonal frequency division multiple access (OFDMA) is considered as the multiple access system for next generation wireless communications and provides multichannel structure. The results of this paper can be divided into two folds. First, the basic equation for multichannel OFDMA slotted ALOHA is devised considering the maximum number of allowed retrials, retransmission probability and the number of users involved in collisions. It is shown that the basic result is independent of retransmission probability as well as the number of users involved in the collision. In the second fold of the paper, we obtained the optimum number of channels with the variation of new packet arrival rate and the maximum allowed number of reattempts, under two conditions. These two conditions are: the system is stable, and provides maximum throughput.

In future cellular networks, random users' mobility as well as time-varying multimedia traffic activity make cellular networks design a challenging task. To efficiently utilize the limited wireless spectrum, it is crucial to enable cellular systems to reactively and dynamically reconfigure cells' service area and capacity. This paper proposes an effective dynamic directional cell coverage adaptation scheme combined with a rate adaptation scheme that together are aimed maximizing radio resource utilization of Wideband Code Division Multiple Access (WCDMA) systems. This approach has the capability of reconfiguring the cell coverage area online by being aware of the system conditions. It takes into account the load on the uplink direction and the pilot power allocation on the downlink direction. Simulation results show the effectiveness of the proposed scheme in increasing WCDMA system efficiency.

Energy-efficient use is a critical issue in the design of wireless multi-hop networks such as wireless ad hoc and sensor networks. Location-based routing protocols are known to have high efficiency, robustness, and scalability and are suitable to be deployed in wireless multi-hop networks. In this paper, we present the design of an energy-efficient localized geographic forwarding algorithm. The design objective is to prolong the lifetime of wireless multi-hop networks. To achieve this goal, our algorithm design employs the strategies of localized implementation of Dijkstra's algorithm and energy criticality avoidance when making decisions on next hop selections for packets forwarding. Simulation results demonstrate that our designed algorithm can achieve high performance in terms of network lifetime.

Abstract Multi‐protocol label switching (MPLS) is considered as the future routing technology of the Internet. Service providers with MPLS‐enabled core infrastructure benefits from the capabilities of this promising protocol to offer incremental value‐added services to their end clients. Virtual private network (VPN) is among many of the services provided by MPLS. Security is not guaranteed with VPN implementation, but it is implied, that is, the users expect to receive a secure connection. Two security concerns of importance for VPNs are customer edge (CE) and provider edge (PE) security. The customer edge is the connection from the customer site to the provider's site. PE is the connection between two providers' site. In this paper, we describe testbed experiences and procedures to study security issues in provider edge MPLS/BGP VPN networks. First, we investigate security constraints in configuring a BGP/MPLS VPNs where the provider's core transport infrastructure supports MPLS. Secondly, we consider the use of GRE tunnel with IPsec in the case where no MPLS support exists in provider's infrastructure. We present the performance results on establishing a secure VPN between two PEs in terms of protocol packet overhead and latency. Copyright © 2008 John Wiley & Sons, Ltd.

With the explosive traffic growth of WDM-based transport networks, the development of GMPLS (or multi-granularity)-based transport networks becomes essential to cope with the network scalability problems. Much work has been devoted to the development of Multi-Granular Crossconnect (MG-XC) architectures and planning (or dimensioning) methods. Extending these efforts here, we are defining a novel problem of planning GMPLS-based transport networks by (1) considering the whole traffic hierarchy defined in GMPLS; (2) allowing bifurcation of multi-granularity traffic demands among different physical routes. We will call such a problem the Routing and Multi-Granular Paths Assignment (RMGPA). The objective of the problem is to minimize the total weighted node port count. Due to the computational complexity of the problem, only very-small-sized problems can be solved exactly through Mixed Integer Linear Programming (MILP) optimization. In this paper, we propose novel heuristics that are capable of solving large-sized problems in a reasonable amount of time.

Wi-Fi mesh networks and WiMAX are two new emerging wireless access technologies for the delivery of broadband services to mobile users in the metropolitan area. To take advantage of the strengths of these two, we propose a novel architecture for next generation wireless metropolitan area networks. In this architecture, no wired backhaul connections for Wi-Fi mesh portals are needed, which considerably reduces the deployment cost and at the same time improves the system scalability. Due to the unique feature of wireless mesh networks which is a part of the architecture, previously proposed mobility management protocol can not work properly in this network environment. We propose a hierarchical mobility management scheme for mobile stations to maintain network connectivity while roaming within the Wi-Fi mesh networks. In this scheme, the dynamic forwarding chain is used to reduce the signalling traffic involved in the mobility management including registration and handoff procedures. The results of the performance evaluation justified the benefits of our proposed mechanism.

Intuitively, identification of nodes close to the network edge is key to the successful setup, and continued operation, of many sensor network protocols and applications. In a previous study [1] we introduced local convex view (lcv) as a means to identify nodes close to the network edge by computing the convex hull of nodes within range. In this paper we evaluate lcv in the presence of position estimation error. Extensive simulations with networks of varying size and topology reveal the surprising observation that lev seems unaffected by estimation error. Motivated by this observation we enumerate a complete set of base node configurations seen by lcv. An analysis reveals that lcv is immune to two of these configurations. Further simulations show the frequency of false-positives and false-negatives imposed by a third, ambiguous, configuration to be low. The frequency of the ambiguous case is 10% in the worst case, for all networks tested. We conclude that the geometric properties underlying lcv are responsible for its resilience to error.

Wireless Sensor Networks (WSN) are becoming a viable tool for many monitoring applications. These applications may be of critical nature where the transportation of the information of events from the region of interest to some base station is crucial, where the data loss can not be tolerated. In the cluster-based two-tier WSN, where cluster-head nodes gather data from sensors in their clusters and then transmit to base station, when cluster head nodes start to die, the coverage of those clusters is lost and it leaves the region unmonitored. Even if the cluster heads are rotated and reassigned after some time, until the next rotation that cluster in question will be out of cluster head and will lose coverage. A lot of information is lost which is sensed and sent by the sensor nodes of the cluster to the dead cluster head. We propose here to select backup cluster heads (BCHs), for those cluster heads which are close to deplete their energy. The cluster head, when about to die, sends an SOS with the gathered information until then, to the respective BCH which takes over the responsibility and continues to work as a new cluster head. To evaluate the effect and results of BCH we used LEACH-C protocol and compared the data loss ratio with and without a BCH.

With the explosive traffic growth of WDM-based transport networks, the development of GMPLS (or multi- granularity)-based transport networks becomes essential to cope with the network scalability problems. This paper defines a novel problem of planning realistic GMPLS-based transport networks by (1) considering the whole traffic hierarchy defined in GMPLS; (2) allowing optical signal conversion at all granularity levels; (3) imposing optical reach constraint on the length of all- optical paths. We will call such a problem the routing and multi- granular paths assignment (RMGPA). The objective of the problem is to minimize the weighted port count in the transport network. Due to the computational complexity of the problem, only very-small-sized problems can be solved exactly through mixed integer linear programming (MILP) optimization. In this work, we propose novel heuristics that are capable of solving large-sized problems in a reasonable amount of time.

Capitalizing on the unifying capabilities of IP, future wireless network operators (WNO) will be able to deploy heterogeneous wireless networks (HWNs). The heterogeneity will enable users to continuously connect to the technology that best meets the users' application requirements. It will also allow WNOs to change the associations of users to attain certain operational objectives. Despite the possible employment of cost reduction mechanisms based on long term observations, we argue that the user-centric nature of HWNs and the possible permutations of triggers for vertical handoffs (VHs) may effectively render user assignment beyond the WNO's control. In this paper, investigate the potential of a module dedicated to reduce the cost of service delivery. In doing so, we discuss the considerations of such a module, including the factors affecting the cost of service delivery and the elements involved in identifying and selecting users to undergo a forced VH.

Location-based routing has been a critical and efficient routing strategy in large wireless sensor networks (WSN) with mobile sinks. However, the performance of location-based routing highly depends on how position information of mobile sinks are managed and updated. This is typically the task of location service. In this paper, we present the design of a hierarchical location service for WSNs with mobile sinks. The main design objective is to greatly reduce the communication overhead for providing location service while maintaining high routing performance. Detailed simulation results are used to verify the high performance of our designed location service.

This paper proposes a multi-channel medium access control (MAC) protocol for wireless mesh networks (WMNs) by using busy tones to prevent data packet collisions at data channels. Multi-channel MAC schemes can achieve higher network throughput than single channel MAC schemes in multi- hop wireless networks. It is especially appealing to exploit multiple channels in WMNs which has high capacity requirement to support backbone multimedia applications. Most previously proposed MAC protocols make use of the RTS/CTS mechanism to deal with data packet collisions caused by exposed/hidden terminal problems in multi-hop environment. However, when multiple channels are used for data transmissions, the traditional RTS/CTS mechanism can no longer handle the exposed/hidden terminal successfully. By investigating the special features of WMN architecture, we apply the busy tone solution into the medium access control mechanism for WMNs, in which mesh nodes have no limit on power consumption. In this paper, we clearly presented the idea and operation of our proposed multichannel MAC protocol for WMNs. Comprehensive simulations are conducted to investigate the effects of various factors on the system performance. Also, the performance of our proposed mechanism is compared with that of previous RTS/CTS-based MAC protocols.

Extensive research work has been done to improve the performance of micro-mobility management schemes on handling fast moving mobile hosts within a local administrative domain. However, most of previous work is focused on reducing the location update cost and handoff latency, without considering any integrated form of quality of service (QoS). With the advancement of wireless access technologies and emergence of numerous multimedia applications over Internet, mobile users require not only the seamless mobility support but certain level of QoS guarantee. Multiprotocol Label Switching (MPLS) protocol has been developed as the solution to IP quality of service, gigabit forwarding, network scaling, and traffic engineering in Internet core network. Motivated by the advanced characteristics of MPLS technology, in this paper, we propose a MPLS-enabled micro-mobility management protocol which aims to enhance the end-to-end QoS provisioning and traffic engineering capabilities while dealing with intra-domain movement in all-IP future generation wireless networks.

Shared-backup path protection (SBPP) has been widely studied in the GMPLS networks due to its efficient spare capacity sharing and flexibility in service provisioning. This paper presents a model for evaluating the end-to-end (E2E) availability of an SBPP connection by assuming that no more than two simultaneous failures could possibly occur in the network. To minimize the redundancy while meeting the E2E availability requirement, a framework of partial restoration from any unexpected failure is created. Based on the proposed availability model, a novel Linear Program (LP) formulation is introduced, which aims to perform the spare capacity allocation for SBPP connections. A new availability-aware spare capacity reprovisioning (SCR) architecture is then introduced for dynamic provisioning of SBPP connections. Extensive simulations are conducted to validate the proposed availability model and demonstrate the effectiveness of the SCR architecture.

The exponential growth in Internet technology has challenged service providers to provide multicast based services like broadcast TV, video on demand and streaming music services over the broadband access infrastructure to their end clients. To meet these requirements, service providers are making use of multi-protocol label switching (MPLS) to better provision and support these bandwidth demanding applications for their end clients. This article presents a performance analysis for the transport of multicast services across MPLS infrastructure networks. Multicast flows are carried using virtual private LAN services (VPLS) as transport media. We further investigate the reliability of multicasting over VPLS and compare it with PIM interms of jitter and delay experimentally using our optical networks research lab (ONRL) testbed.

In this paper, we introduce a reactive congestion control scheme for wideband CDMA (WCDMA) cellular networks and study its performance with respect to network throughput and call dropping rates. This scheme utilizes the idea of directional cell breathing (DCB), in which network cells are partitioned into N-sectors where each sector is served by a directional smart antenna. We propose a heuristic algorithm called directional cell breathing based-reactive congestion control (DCBB-RCC) that controls the transmission power of the common pilot channel (CPICH) such that the coverage area of a cell sector can dynamically be extended towards a nearby loaded sector or shrunk towards cell center for a loaded sector. Therefore, this mechanism activates a handoff procedure to shift some traffic of a loaded cell towards a lightly loaded cell. The effectiveness of our proposal is investigated through snap shot simulation using numerical examples.

Providing loss rate guarantees for priority-guaranteed classes while making bursts of the best-effort class pass through is an important absolute QoS issue in OBS networks. Based on Preemptive Scheme with Best-Effort Class Support (PSBES), in this paper, we propose several schemes, which integrate PSBES and wavelength grouping schemes and aim at keeping the loss rates of priority-guaranteed classes under their respective upper bounds when traffic load gets heavier. Simulation results show that the integrated scheme of PSBES and modified dynamic wavelength grouping performs the best among the proposed schemes.

A novel fault-localisation protocol is constructed based on the principles of distributed control and management mechanisms. The proposed protocol has high scalability and speed, but at the cost of increased computational complexity. To provide the maximum level of transparency, the protocol skips any optical power monitoring or spectrum analysis at the intermediate nodes of established lightpaths. Moreover, to narrow down the associated time and space complexities, it restricts the fault-localisation area to a small area called limited-perimeter. These functions are implemented by means of five phases, namely pausing, flooding, multicasting, matching, and concluding. Although the protocol has been developed to pinpoint single failures, it could track down multiple failures that occur in nonoverlapped limited-perimeters. To evaluate the performance of the proposed method, time and space complexities are calculated and compared with a counterpart protocol that does not limit the fault-localisation area.

Scalability has been a crucial design concern for quality of service routing protocols to be deployed in high-speed communications networks. The issue of bandwidth-constrained widest-shortest path (WSP) routing, which selects the WSP connecting a pair of nodes subject to a bandwidth constraint is studied. The design objective is to enable fast route calculation in identifying such constrained paths. To achieve this goal, a polynomial optimal algorithm using bidirectional search is designed. The complexity of the designed algorithm is deduced to be O(|E|lg|V|), where |E| and |V| represent the number of links and nodes in the network, respectively. Simulation results demonstrate that the designed algorithm can significantly reduce the average-case computational overhead caused by the calculation of such constrained routes as compared with related work.

Mapping the end to end QoS requirements into link QoS requirements is an important step for resource allocation of connection oriented services. The problem of the QoS partitioning has been addressed in literature and proved to be NP complete. Different algorithms are proposed to solve the problem of single end-to-end QoS metric. However, these algorithms are near optimal or heuristic algorithms and solve the QoS partitioning problem for single QoS metric. In this paper, we propose a novel optimal partitioning algorithm which is capable of partitioning the end to end QoS requirement for multiple QoS metrics, additive and multiplicative, simultaneously. Extensive simulation verified the effectiveness of the algorithm compared to two QoS partitioning algorithms. The results show that the proposed algorithm outperforms the other two algorithms for loose and stringent QoS requirements and over different path lengths.

The rapid growth in internet technology has motivated service providers to consider deploying multicast based services like TV broadcast, Video on demand and streaming music services over the broadband access infrastructure to their customers. In having Multi protocol Label Switching (MPLS) as the core infrastructure protocol, providers are motivated to keep this type of service reliable to their customers. Three key challenges for delivering these services need to be taken into consideration: 1) Transport bandwidth Efficiency 2) Service Performance 3) Quality of Service associated with multicast application. In this article, we investigate performances of QoS Metrics and reliability using Virtual Private LAN Services (VPLS) as transport media for multicast services. We describe experiments related to the deployment of multicast services in a VPLS network testbed, such as delivery of high-quality video and audio conferencing. We further investigate the performance and reliability of multicasting over VPLS experimentally using our Optical Networks Research Lab [ONRL] testbed.

The mainstream dynamic bandwidth allocation (DBA) architectures for Ethernet Passive Optical Networks (EPONs) have employed two independent scheduling mechanisms in order to support quality of service: inter-ONU scheduling (timeslot assignment) and intra-ONU scheduling (priority queuing). These architectures tend to implement the inter-ONU scheduling function at the OLT, whereas the intra-ONU scheduling function at the individual ONUs. Since these scheduling functions have been separated, these architectures cannot generally yield a globally optimized bandwidth allocation. In this paper, a centralized bandwidth allocation model is proposed that implements both the scheduling functions at the OLT. A credit pooling technique is employed that enables the OLT to partition the upstream bandwidth among different class of service queues, and to prevent ONUs from monopolizing the bandwidth. High network utilization is achieved by embedding ONU scheduling decisions in time and by eliminating the channel idle-time overhead, associated with many earlier DBA schemes.

Additive Increase Multiplicative Decrease (AIMD) window adjustment mechanism has been embedded in TCP in order to regulate the transmission rate in modern communication networks. In recent years, the AIMD (1,0.5) traffic regulation mechanism along with possibly additional enhancements, such as false timeout detection and explicit notification, has been considered in the carriers with Optical Burst Switching (OBS) as the underlying transmission technology. This paper introduces a novel rate control mechanism based on Generalized AIMD (α,β), called Burst AIMD (BAIMD), for tuning the rate control parameters (α, β) at each sender. BAIMD is designed to improve throughput while maintaining friendliness with co-existing AIMD (1,0.5) flows, and is characterized in the following two folds: (1) no burst window is required in the TCP sender's level; (2) no explicit notifications are required. The above characteristics make the proposed scheme distinguished from all the past reported counterparts by minimizing the signalling efforts and control complexity. The simulation result shows that BAIMD can solidly outperform the past reported AIMD-based (1,0.5) rate control schemes under a wide range of traffic loads. We also suggest that BAIMD rate control mechanism may serve as a better choice than AIMD (1,0.5) in the bufferless OBS networks due to its dynamic and flexible (α,β) parameter pair.

Vertical Handoffs occur when a user changes association from one type of wireless access technology to another while maintaining an active session. Much work has been done in ensuring seamless handoffs that also preserve QoS. However, service providers can exploit vertical handoffs as a Radio Resource Management (RRM) means to relieve congestion, load balance and uphold QoS requirements. Nevertheless, this exploitation requires rigorous study in order to realize its full potential. In this paper, we advocate the use and study of forced vertical handoffs as a powerful RRM tool. We also discuss the different factors involved in the design and operation a forced vertical handoff module (FVHM). Furthermore, we provide a RRM framework for future wireless network where an FVHM is employed and set to interact with a bandwidth adaptation algorithm. In the framework, we introduce the Willingness function, a novel representation for a user's instantaneous willingness to undergo a forced vertical handoff.

The development of bandwidth-demanding IP multicast applications has made supporting multicasting in optical layer a favorite option. This article examines the dynamic behavior of optical layer multicasting in sparse splitting WDM networks. We proposed a routing algorithm incorporating the Member-only and shortest-widest approaches to achieve the objectives of Quality of Service (QoS) and traffic engineering in dynamic environment, assuming reasonable blocking probability. A Bottle-neck First-Fit wavelength assignment approach was introduced and applied. The study compared the simulation results of the proposed algorithm to that from the shortest-path based Member-only approach. It showed that the proposed algorithm balances traffic loads well, and accommodates more connection requests in low and medium loads. We further investigated the effects of limiting wavelength usage for each forest on overall blocking probability. Moreover, we formally proved that the algorithm can be easily extended to meet the bandwidth requirement.

Applications and users require different recovery services. Some applications are delay sensitive and demand fast restoration, while others are data sensitive and require 100% data recovery. Dynamic restoration techniques, on the other hand, have exclusive restoration abilities in terms of latency, restoration throughput, and complexity. It is therefore important to comprehend the diversity among dynamic restoration techniques in order to effectively mesh their aptitudes to applications requirements. Accordingly, in this paper we evaluate distinct types of dynamic restoration approaches, namely disjoint path, partially joint path, and link restoration to identify their specialty and deficiency in terms of blocking probability, restoration delay, and computational complexity. Our results reveal that partially joint path restoration always obtains the lowest blocking probability. Nevertheless, this scheme has the highest computational complexity. Link restoration is the fastest if fast fault localization is achieved ahead of the restoration process. Conversely, disjoint path restoration always has the highest average restoration delay. However, this approach is the simplest and obtains the lowest computational complexity.

Much of the literature have mainly investigated the seamlessness and the effects of Vertical Handoffs (VHs), in addition to the design of policy-based Radio Resource Management (RRM) models that cater for their unique characteristics. However, VHs can be viewed as a powerful RRM tool. A service provider may force users to handoff to other networks in a coverage overlay to relieve congestion or balance the load. In this paper, we present a novel multi-class, subadaptation module for forced vertical handoffs. We discuss added arguments required by the multi-class setting, and show the flexibility of our model through its capability to meet different objectives for different service providers.

In this paper, we outline the basis of a novel cooperative module for congestion control and load balancing in WCDMA networks. Through carefully exploiting the capabilities of smart and directional antennas, we propose a controllable directional breathing where a base station's (BS) sectorized coverage is varied reactively in instances of congestion, and proactively in instances of exercising load balancing. This proposal, called Directional Cell Breathing (DCB), overcomes the drawbacks of non-sectorized and non-controllable WCDMA breathing management by optimizing the coverage level within each sector under constraints minding sectoral traffic load and interference bounds. Interference analysis is carried out to determine the eligibility of a cell to be considered in DCB if one of its adjacent cells becomes overloaded. This analysis is then used in a mathematical formulation to facilitate the optimization of the proposed scheme.

Summary form only given. Shared protection aims to provide the same level of protection, against a single link failure, as the dedicated one while using less network resources. In this paper, we present the issue of survivability in a time slotted optical networks deploying DWDM. To guarantee the recovery and to maintain the performance of the service, sufficient resource needs to be available at the setup time of the protection. However it is possible to optimize the protection capacity. Indeed the primary traffic is composed of a set of flows, which may be going through different paths. Therefore a protection could be found using just enough resources by sharing the backup among many flows. We propose here a technique to identify and provision the protection using the minimum necessary resources. In particular, we present an algorithm that computes the optimal protection required for a primary traffic from a source to a destination, and the maximum capacity that could be used, on each link, for the protection. We prove through simulation results that this shared mesh protection scheme can significantly reduce the required network protection capacity.

This paper presents a new paradigm to enhance the cluster stability and support the route reliability in the cluster-based ad hoc routing protocols. This paradigm is based on providing a secondary clusterhead (SCH) for each clusterhead, which we call here primary clusterhead (PCH). This SCH, which is a regular member node, is identified and assigned by its PCH to be the future leader of the cluster. The SCH will be triggered to be the PCH when the former PCH can no longer be a clusterhead. To enhance the cluster stability, this paradigm introduces a new protocol to reform the cluster, namely the smooth and efficient re-clustering (SERC) protocol. In SERC, since the future clusterhead is known by the cluster members, the cluster leadership will be transferred smoothly and the cluster will be reformed immediately with no need to invoke the clustering algorithm. To support the route reliability, this paradigm provides a new multipath routing protocol, which is named a localized cluster-based rerouting and resource reservation protocol (LC3R). In LC3R, the main route can be established through the PCH chains, while the backup route can be established through the SCH chains. In this study, we show how the SERC/LC3R works and how this paradigm can achieve a high packet delivery rate with saving clustering and routing overhead.

Service providers today are constantly seeking to offer multiple services on a single common infrastructure. For instance, it is desirable sometimes to provide transport services transparently to data traffic encapsulated over different network layers. Tunneling is a technique for encapsulating a packet or frame within another packet of the same or a different network layer. One of the motivations for tunneling is bridging various heterogeneous networks that use different protocols for communication. Tunneling is also used for providing private and secure communications over a publicly shared network. This article investigates the interactions between different tunneling technologies in order to provide end-to-end virtual connectivity to end clients. Particularly, the article describes the technical details of the implementation of various layer-2 tunneling techniques-such as L2TP, GRE, and MPLS-based tunnels- in order to establish an end-to-end virtual connection-service as a concatenation of services offered by the different network domains along the path between end users.

Bandwidth adaptation algorithms (BAA) assume an integral role in radio resource management (RRM) frameworks for future wireless networks. Taking advantage of the nature of adaptive multimedia application, they empower system providers with allocation versatility and economic increase. Due to the dynamic nature to be witnessed in future networks, BAA has been set to be trigger at every change in the system state. This burdens the different entities involved in RRM. In this work, the concept of stochastically triggered BAA (STBAA) is proposed. The tradeoff between admission ratios and users satisfaction is evaluated. It is found that considerable gains can still be achieved with the adaptation not fully engaged

Guaranteeing the statistical delay for real time connections is an area of interest for many researchers, consequently, several analytical and measurement based admission control algorithms (MBAC) are proposed. The proposed analytical algorithms provide solutions based on traffic fluid models or service disciplines which do not isolate the different flows at the schedular. The proposed MBAC algorithm can not meet the distinct violation probability requirements of a connection. Thus, in this paper we propose a new MBAC algorithm, which is capable of meeting the distinct violation probability requirement. The algorithm utilizes the weighted fair queueing (WFQ) scheduler that is capable of isolating the traffic flows. The proposed algorithm is different from other MBAC algorithms, since it admits requests based on delay measurement rather than bandwidth measurement as most MBAC algorithms do. This facilitates meeting the distinct violation probability requirement of the connections. The simulation results revealed that the proposed algorithm can admit three times the deterministic algorithm for distinct delay requirements.

In next generation wireless networks, mobile users will roam across different wireless access networks. Mobile IP is employed as the mobility management protocol in the all-IP wireless environment. But mobile IP has scalability problem when dealing with micro-mobility and cannot provision QoS for multimedia applications of mobile users. In this paper, we propose dynamic hierarchical mobile MPLS (DHMM) protocol for micro-mobility management, at the same time facilitating the system with traffic engineering and QoS provisioning capabilities. By employing DHMM protocol in the all-IP wireless access network, the end-to-end delay can be considerably reduced and the traffic distribution in the network can be well balanced through MPLS traffic engineering.

Virtual private LAN services (VPLS) is a new layer 2 (L2) virtual private network (VPN), which allows connection of multipoint customers at the same time. Multi-protocol label switching (MPLS) technology is the most popular candidate for implementing VPLS because it supports traffic engineering (TE) functionality over the established label switching paths (LSP). However, MPLS's TE support is provided over point-to-point (P2P) LSPs. The functionality and signaling of point to multipoint (P2MP) LSPs are not supported in existing MPLS architecture. In this paper, we propose a new on line distributed routing algorithm for supporting QoS bandwidth flow guarantees. The algorithm provides TE functionality over the P2MP VPLS connections in the core MPLS networks. The on-line distributed routing algorithm maximizes the number of admitted requests by avoiding the critical links of other source-destinations sets. The critical links are identified based on the number of times the link is used to route the source-destinations set traffic and the load over the links. The algorithm does not assume any a priori knowledge of the network traffic. The proposed algorithm performance is compared to some existing algorithms such as the widest shortest path (WSP) and the Plotkin algorithms. It shows that it outperforms both algorithms by having lower blocking probability.

In this paper we present a novel architecture which implements sharing of the transceiver pairs between the regeneration sub-system and the local add-drop subsystem of the optical cross-connect. By making minor changes in the existing architecture we can implement our sharable architecture. We show in our work that a sharable architecture can be used to reduce the blocking probability of add-drop connections and also maintain the necessary grade of service for regeneration connections. We present 3 different sharing schemes in this work. By using a sharable architecture we can reduce the net number of transceivers to achieve a desired blocking probability.

Horizontally expanded and vertically stacked optical banyan (HVOB) is a general architecture for constructing banyan-based optical switches. Blocking analysis is an effective approach to studying network performance and finding a graceful compromise among hardware cost, network depth and blocking probability; however, little has been done on analyzing the blocking behavior of general HVOB networks. In this paper, we study the overall blocking behavior of a HVOB network, where an upper bound on the blocking probability of the network is developed. The upper bound depicts accurately the overall performance behavior of a HVOB network as verified by extensive simulation results and it agrees with the strictly nonblocking condition of the network. The derived upper bound is significant because it reveals the inherent relationship among blocking probability, network depth, and network hardware cost, by which a desirable tradeoff can be made among them. In particular, our bound provides network developers an effective tool to estimate the maximum blocking probability of a HVOB network in which different routing algorithms can be applied with a guaranteed performance in terms of blocking probability, hardware cost and network depth. An important conclusion drawn from our work is that the hardware cost of HVOB networks can be reduced dramatically without introducing either significantly high blocking probability or a large network depth.

In this paper, we study the issue of dynamically selecting shortest paths in wavelength-routed networks. We present several fast shortest path selection algorithms for networks with and without wavelength conversions. The presented algorithms employ the strategies of sequential search, backward routing, and informed search. Simulation results demonstrate that our presented algorithms can significantly reduce the average-case running time in identifying shortest paths in wavelength-routed networks.

Medium access control (MAC) is one of the most crucial issues in Ethernet passive optical networks (EPONs). To prevent data of different optical network units (ONUs) from collision in the upstream direction, an EPON system must employ a MAC mechanism to arbitrate access to the shared upstream channel and at the same time efficiently share the bandwidth of the upstream channel among all ONUs. In this paper, we present an adaptive MAC polling protocol for an EPON system. This polling protocol uses an adaptive scheduling algorithm called the earliest-packet-first (EPF) algorithm that schedules the transmission order of different ONUs based on the arrival time of the first packet waiting in the queue of each ONU and always schedules the ONU with the earliest packet to transmit first in each polling. The purpose is to reduce the packet delay in the system and thus provide better quality of service for end users.

In this paper, we design grid-based routing (GBR) protocols for wireless multi-hop networks. The objective is to effectively reduce the protocol overhead for network management with the assistance of position information. GBR divides networks into equally spaced grids. To perform a routing operation, GBR requires as few grids as possible to participate while preserving network connectivity. We design different protocols for different environments and deduce analytical results to observe the high performance of the designed protocols.

The introduction of wireless multimedia applications brought about an attractive characteristic from a resource management point of view, namely the adaptability of such applications. Allocations made to deliver the multimedia applications can be varied depending on the conditions of the user, the network, or both. In a framework for resource management, the role of a bandwidth adaptation algorithm (BAA) is to provision the adaptation of the different users in A cell. Previous proposals for BAA persistently engage the adaptation whenever required. Naturally, this comes at a high system cost. In this work, the novel notion of stochastically triggered bandwidth adaptation algorithms (STBAA) is introduced. The objective of the STBAA framework is to allow system providers to exploit the tradeoff between admission ratios and user satisfaction in order to control the operational cost of adaptation.

No abstract available.

In most MANET clustering protocols, the clusterhead nodes take on a special role in managing routing information. However, the frequent changes of the clusterheads affect the performance of the routing protocol. Eventually, the clustering stability in MANET would be significantly affected. The route between two nodes changes constantly as the clusterhead set changes. Also, since the clusterhead has the recent routing information in the cluster-based routing protocol, a collapse of the cluster leads to loss those information that was stored at its clusterhead. To elect a new clusterhead, exchanging messages to reform the cluster which considered communication overhead are needed. The goal then would be to keep the average cluster residence time for such a node in a cluster as long as possible. This time is defined as the time a node remains associated with a given cluster not a given clusterhead. This can be done by deploying a secondary clusterhead for each clusterhead which we call here primary clusterhead. This secondary clusterhead, which is a regular member node, is identified and assigned by its primary to be the future leader of the cluster. Since the future clusterhead is known by the cluster members, the cluster leadership is transferred smoothly and the cluster is reformed immediately with no need to invoke the clustering algorithm. Hence, the smooth clusterhead transfer from a node to another aims at increasing the cluster residence time which sustains the stability of the network, decrease the clustering communication overhead and minimize the time spent by each node to join or to reform a cluster.

A vertical handoff describes the event when a mobile terminal changes its association from one type of wireless access technology to another, whether or not the networks involved belong to one provider. Of the many intricacies yet to be understood in heterogeneous wireless networks is the exact effect of vertical handoffs due to different triggers. In this paper, an attempt is made to dichotomize the interaction of preference-triggered vertical handoffs and joint allocation policies. A general framework for evaluating allocation policies in heterogeneous environments is described. Models for disjoint and joint resource management are developed. Adequate admission control policies are also presented. It is found that, even though a joint allocation policy does enhance service delivery to new-call requests, handoff-call requests may undergo slight negative effects.

Ethernet passive optical networks (EPONs) have emerged as the one of the most promising candidates for next-generation access networks. These new architectures couple low-cost optics with advanced edge electronics to offer vastly improved scalability over competing digital subscriber line and cable modem offerings. This paper proposes several novel architectural enhancements for EPON, which will help increase the viability of optical access over a broader range of subscriber access scenarios. Specifically, this paper proposes a two-stage EPON architecture that allows more end-users to share an optical line terminal link, and enables longer access reach/distances (beyond the usual 25 km distance). In addition, a new dynamic bandwidth allocation (DBA) algorithm is proposed to effectively allocate bandwidths between end users. This DBA algorithm can support differentiated services in a network with heterogeneous traffic. We conduct detailed simulation experiments to study the performance and validate the effectiveness of the proposed architecture and algorithms.

This work proposes a new reservation protocol for enhancing the performance of wavelength-routed networks. To be more robust and reliable, the proposed approach employs distributed control mechanisms. The new method particularly focuses on wavelength-division multiplexed (WDM) core networks with distant end-nodes. It takes into account the considerable amount of data that can be transferred by high-speed WDM networks within limited reservation periods. To increase the throughput, the protocol consumes the unoccupied bandwidth of reservation phases by transferring nonreal-time data packets during these intervals. This scheme is implemented by applying a modified form of backward reservation protocol. To initiate a multihop reservation call, this protocol labels a path as reserved instead of locking it. Meanwhile, labeled nodes with single-hop requests will receive permission signals to send predetermined packet sizes. The length of packets transmitted is defined by the round-trip propagation delay between the current and the upcoming nodes along the path. In case a reservation fails, already labeled nodes will be notified by receiving a prevention signal, which will block them from transferring data packets.

Hybrid hierarchical optical cross-connects leverages the benefits of both all-optical (OOO) and optical-electrical (OEO) switching for a cost-effective solution in future optical networks. The design goal using hybrid cross-connects is to minimize the sum of two cost metrics: OEO switching cost and OOO switching cost. This paper proposes two different waveband merging architectures and minimum cost routing and merging algorithms for offline traffic scenario. The simulation based results show that the proposed algorithms provide higher cost benefit as compared to existing algorithms that do not rely on waveband merging architecture.

This paper investigates the problem of optimal diverse routing for shared path-based protection in the complete routing information scenario on mesh optical networks, where a novel Integer Linear Programming (ILP) formulation is introduced such that the least-cost link-disjoint working and protection path-pair can be derived in a single step. The proposed ILP formulation is characterized by the facts that it is solvable with the commercially available Linear Programming (LP) solvers and that it can deal with the dependency between working and spare capacity in the network, which is a step ahead of the most state-of-the-art techniques in the design of diverse routing algorithms for shared protection. To verify the proposed ILP, an experiment is conducted to compare it with four reported schemes for end-to-end shared protection on two network topologies, namely APFPBC, MLR, ITSA, and ILP-2S, where blocking probability is taken as the performance metric with connection requests being dynamically launched into the networks. The simulation results show that the ILP formulation yields the best performance while the ILP-2S scheme investigating less network states yields the worst. We also use the results by the proposed ILP to evaluate the four heuristic-based schemes adopted in the simulation in terms of two performance indexes – the percentage of optimality (denoted as %opti) and the offset of optimality (denoted as Q).

One of critical issues of today's optical network planning is how to implement a dynamically reconfigurable optical transport layer coupled with suitable control and management protocols. This paper presents a novel distributed connection management protocol with reconfiguration capabilities for data-centric optical networks. A novel concept of a "token-based" distributed algorithm to reroute existing connections to optimal paths after a failure recovery is introduced. The performance of the proposed protocol is evaluated and compared via simulation in a distributed control environment.

Power use is a crucial issue in wireless ad hoc networks since mobile hosts are typically battery-constrained. This paper presents a localized power-efficient routing protocol, which aims at improving the power-use efficiency of traditional ad hoc routing protocols. Our protocol works by introducing recursive localized power-use optimization at intermediate nodes on routes that a traditional routing protocol returns either proactively or reactively. For this purpose, each network node maintains the state information of its one-hop neighborhood. Simulation results demonstrate that the designed protocol can significantly improve the power use efficiency of traditional protocols. The simplicity, low overhead, and high efficiency in power utilization make the designed protocol suitable for providing scalable power-efficient routing support in wireless ad hoc networks.

This paper presents the design of a position-aided on demand routing (PAR) protocol. The objective is to effectively reduce the communication overhead associated with path discovery and maintenance with the assistance of position information. For this purpose, PAR employs a novel restricted directional flooding mechanism. This mechanism creates an ellipse-forwarding zone, across which control messages are propagated for route discovery. Moreover, PAR uses location-guided expanding ring search, which works by searching successively larger areas for paths. This searching strategy can effectively prevent unnecessary network-wide flooding. In terms of location tracking, we design a method of recursive passive listening at intermediate nodes for end-to-end location tracking. This method enables the source to effectively keep track of the up-to-date location of its communication partner at little control overhead. Simulation results demonstrate that the PAR protocol can significantly reduce the communication overhead associated with path discovery, compared with related work.

This paper proposes a multi-initiation mechanism for dynamic path restoration to handle single-link failures in GMPLS-based WDM networks. This mechanism allows multiple network nodes on the primary path of a disrupted connection to participate in the restoration of the disrupted connection. Each of the nodes respectively initiates a restoration process upon the detection or notification of a link failure. In each of the processes, the initiating node attempts to dynamically establish a backup path for the disrupted connection. The destination node acts as a coordinator among multiple restoration processes. The purpose is to reduce the path restoration time so that a backup path can be provisioned more quickly for each disrupted connection that traverses a failed link. Based on this mechanism, a path restoration protocol is then presented and the performance of the protocol is evaluated through simulation experiments in terms of path restoration time and path restoration probability.

Analytical and simulation techniques are presented to investigate the impact of multiple link failures on the availability performance of class sharing, pool sharing, and dedicated mesh restoration schemes. Formulations are given to synthesize distributed point-to-point traffic that is used in the analysis and simulation studies. It is shown that the availability of backup resources is a function of the number of "troublesome" links along the working paths of demands that share these resources. It is also shown that demands can receive a carrier grade service only when they are routed over very short distances with working paths not exceeding 2 hops.

Shared protection aims to provide the same level of protection, against failure, as the dedicated one while using less network resources. In this paper we present the issue of survivability in a time slotted optical networks deploying DWDM. To guarantee the recovery, sufficient resource needs to be available at the setup time of the protection. However it is possible to optimize the protection capacity. Indeed the primary traffic is composed of a set of flows, which may be going through different paths. Therefore a protection could be found using just enough resources by sharing the backup among many flows. We propose here a technique to identify and provision the protection using the minimum necessary resources. We prove through simulation results that this shared mesh protection scheme can significantly reduce the required network protection capacity

In fourth generation (4G) wireless networks, users are able to roam freely from one type of wireless access network to another while preserving the main characteristics of their connections. While various aspects of this vision have been discussed since mid 1990s, there remain fundamental challenges. Of these challenges is performing resource management across different access networks while considering various irregularities. This work advocates that any proposal for resource management in such networks should act reactively toward operational dynamicity while proactively allocating resources in a manner that sustains demand uncertainty. It shows how proactive allocations can be made using a formulation based on stochastic programming. The objective is to maximize the allocations while minimizing underutilization and rejection. It also discusses how a comprehensive proactive module can be realized. To the best of our knowledge, this is the first attempt to directly address joint resource management in wireless heterogeneous networks.

Energy use is a crucial design concern in wireless ad hoc networks. The design objectives of energy-aware routing include selecting energy-efficient paths and minimizing the protocol overhead incurred in acquiring such paths. To achieve these goals altogether, we present the design of two energy-aware on-demand routing protocols for different network environments. The key idea behind our design is to adaptively select the subset of nodes required to involve in a route-searching process to acquire a high residual-energy path or the degree to which nodes are required to participate in the process of searching for a low-power path for networks wherein nodes can adaptively adjust their transmission power: Analytical and simulation results are given to demonstrate the high performance of the designed protocols in energy-efficient utilization and in reducing the protocol overhead incurred in acquiring energy-aware routes.

In this paper, a survivable routing algorithm is proposed for shared segment protection (SSP), called optimal self-healing loop allocation (OSHLA), which dynamically allocates spare capacity for a given working lightpath in mesh wavelength-division-multiplexing (WDM) networks with partial wavelength conversion capability. Two novel graph transformation approaches, namely graph of cycles and wavelength graph of paths, are introduced to solve this problem, in which the task of survivable routing is formulated as a series of shortest path searching processes. In addition to an analysis on the computation complexity, a suite of experiments is conducted to verify OSHLA on four networks with different topologies and traffic loads. We find that the blocking probability and computation complexity are dominated by the upper bound on the length of the working and protection segments. Comparison is made between OSHLA and four other reported schemes in terms of blocking probability. The results show that OSHLA can achieve the lowest blocking probability under the network environment of interest. We conclude that OSHLA provides a generalized framework of survivable routing for an efficient implementation of SSP in mesh WDM partial wavelength convertible networks. With OSHLA, a compromise is initiated by manipulating the upper bound on the length of working and protection segments such that the best performance-computation complexity gain can be achieved.

Metropolitan area and long-haul networks are migrating toward the deployment of optical mesh technologies. This requires, among other things, a new generation of highly intelligent protection and restoration mechanisms to perform functions of protection and bandwidth management. We introduce an architecture that provides differentiated protection services across multiple layers of network hierarchy. A connection at any client layer can request a protection against resource failures at any lower layer. A key aspect of the architecture is the hierarchical tree organization of shared risk link group (SRLG) resources. They represent routing-related failures across all layers of protocol stack. The architecture is very scalable in terms of communicating link-state and bandwidth information between adjacent layers. SRLG trees are used to aggregate this information and provide a summary to the client layer. We discuss the requirements and challenges for routing and signaling mechanisms in order to support the proposed architecture. The complexity of this architecture is evaluated and compared with the complexity of a nonhierarchical alternative.

This paper introduces a novel approach, called Short Leap Shared Protection with spare capacity Reallocation (SLSP-R), to deal with dynamic reconfiguration of spare capacity for MPLS-based recovery in the Internet backbone networks. SLSP-R is based on the SLSP framework and is designed to quantify the impact of computation complexity on network performance. The basic idea for SLSP-R is to subdivide a lengthy optimization process into several subtasks in order to trade the optimization quality with computation time. For this purpose, we compare three strategies for grouping working paths before an integer programming (InP) formulation is solved, namely, the Most Overlapped, Most Diverse, and Randomly Distributed. Analytical modeling of the problem is provided to show the feasibility of the subgrouping strategy. A numerical experiment as well as simulation-based study are conducted on four networks with different topology to evaluate the SLSP-R algorithm. The design methodology to determine the size of each subset of working paths is verified in the simulation.

This paper proposes a suite of approaches to solve the survivable routing problem with shared protection. We first define in mathematics the maximum extent of resource sharing for a protection path given the corresponding working path according to the current network link-state. Then the problem of solving the least-cost working & protection path-pair (in terms of the sum of the cost) is formulated into an Integer Linear Programming process. Due to the dependency of the protection path on its working path, however, the formulation is not scalable with the network size, and takes an extra effort to solve. Therefore, we introduce two heuristic algorithms, called Iterative Two-Step-Approach (ITSA) & Maximum Likelihood Relaxation (MLR), which aim to explore the approximating optimal solutions with less computation time. We evaluate the performance of the proposed schemes, and make a comparison with some reported counterparts. The simulation results show that the ITSA scheme, with a properly defined tolerance to optimality, can achieve the best performance at the expense of more computation time. On the other hand, MLR delivers a compromise between computation efficiency & performance.

This paper provides a suite of approaches to solving the survivable routing problem with shared protection. The problem diverse solving the least-cost working and protection path-pair (in terms of the sum of the cost) is formulated into integer linear programming. We also introduce two heuristic algorithms, called iterative two-step-approach (ITSA) and maximum likelihood relaxation (MLR), which aim to finding the approximating optimal solution within a limited amount of computation time. We examine the performance of the proposed schemes and make a comparison with some reported counterparts. It is observed that the ITSA scheme with a properly defined tolerance to the optimality can achieve the best performance at the expense of much longer computation time. MLR can provide an ultra-fast path selection process, which behaves as a good tradeoff between computation efficiency and performance.

In this paper, we propose an approach of optimal protection domain allocation, called OPDA (optimal protection domain allocation), for dynamically allocating spare capacity for a given working lightpath in WDM networks with partial wavelength conversion capability. The optimization process is formulated as a shortest path searching problem in a transferred graph of cycles and wavelength graph of paths. We conduct a series of experiments to verify the proposed approach on four networks with different topologies and traffic load. We conduct experiments to compare the blocking probability of using OPSA with four reported schemes. The results show that OPDA achieves the best performance.

On the contrary to present conjectures, our medium access control (MAC)-based performance studies revealed that battery capacity may not be used as the sole means for achieving energy-based fairness and system longevity for wireless mobile multi-hop ad hoc and sensor networks. Moreover, energy conservation may be attained only if valuable MAC (and PHY) input is passed to the network layer. Hence, in this paper, we propose two schemes the objective of which is to enhance the operation of existing power-based multi-path routing protocols via cross-layer designs and optimal load assignments. Our proposed schemes, namely, energy-constrained path selection (ECPS) and energy-efficient load assignment (E2LA), employ probabilistic dynamic programming techniques and utilize cross-layer interactions between the network and MAC layers. To the authors' best knowledge, this is the first time that MAC-originated information is used as the basis for achieving energy-efficient routing.

In this paper, we propose the multichannel variable-radius multiple access (M-VRMA) scheme for power-controlled multichannel medium access control (MAC) in mobile ad hoc networks. We propose the RTS/object-to-sending (OTS)/VP-CTS (ROV) protocol based on M-VRMA, multiple access with lag time, OTS, and VP-CTS for efficient variable-radius supports in heterogeneous ad-hoc networks, without relying on busy-tone or any mechanisms that require expensive specialized hardware or more than one transceivers per device. Our simulation results demonstrate that for the same radio bandwidth, ROV can achieve considerably higher throughput as compared to fixed-radius IEEE 802.11 or previous power-controlled RTS/CTS protocols without variable-radius supports.

In this work, we design a destination-initiated protocol, which aims at building source-rooted shortest path tree (SPT) in a hop-by-hop manner for providing scalable multicast. The designed protocol can support group applications with dynamic membership well. Performance analysis and simulation results show that the destination-initiated characteristic can significantly reduce the computation, storage and communication overhead associated with SPT constructions.

The multicast forwarding state scalability issue is one of the critical issues that delay the deployment of IP multicast in the global Internet. With traditional protocols, each router is required to maintain a forwarding entry locally for each group whose distribution tree passes through the router itself. Consequently, the number of forwarding entries at routers increases linearly with the number of concurrent ongoing multicast sessions. This can pose the forwarding state scalability issue when the number of multicast sessions is very large. The paper addresses this scalability issue in providing efficient delay-constrained multicasting in IP networks. We propose a scalable multicast routing heuristic. Its computational complexity is deduced to be O(m|V|/sup 2/), where m is the size of the multicast group and |V| is the size of the network. In particular, if the heuristic is executed online, its computational complexity can be further reduced to O(m/sup 2/). This property makes the heuristic scale well with the number of concurrent sessions since multicasting subject to a delay constraint is typically executed on a per-session basis. Simulation results show that the proposed heuristic can achieve high performance in reducing the forwarding state at routers and in utilizing network resources efficiently.

In this paper, we solve the survivable routing problem in dynamic WDM mesh networks under the framework of short leap shared protection (SLSP). A novel algorithm called cascaded diverse routing (CDR) is proposed. We also demonstrate a novel approach to solving the diverse routing problem in networks with dynamic traffic for the purpose of shared protection, called iterative two-step-approach (ITSA). Simulation is conducted using four different networks (22-, 30-, 79-, 100-node) for a comparison between ordinary shared protection schemes and the SLSP scheme. Simulation results show that the best performance can be achieved with well-design diameter of protection domains for every connection request according to the size and topology of the network.

This paper proposes a scalable design for next-generation optical cross-connects (OXCs), where a novel strategy for dimensioning the network switching capability as a long term planning is presented. When traffic demand grows, the proposed scheme simply expands the switching capacity of OXCs in waveband- and fiber-switching tiers. To minimize the number of extra fibers for waveband- and fiber-switching tiers required to satisfy a given traffic matrix, we formulate the problem of routing and wavelength assignment with tunnel allocation (RWAT) into two integer linear programming (ILP) processes that are performed sequentially. Experiments are conducted on two sample networks to compare the throughput and the number of switch points when the networks adopt different switching architectures with different traffic loads. We conclude that the proposed optimization scheme can dimension the networks with expandability and scalability to the growing traffic demand.

The intricate problem of energy conservation in wireless ad hoc networks is of great significance due to the limited battery capacity of the participating mobile devices. In this paper, we propose a novel framework, namely quasi-guaranteed system lifetime (Q-GSL), which allows the admission of flows without jeopardizing the limited energy of the wireless stations. A noteworthy feature of Q-GSL is that it provides a means for contention mitigation and load balancing. The upper bound on the packet rate is computed in the absence of the energy overheads associated with routing, contention resolution, channel sensing, etc. Hence, the upper bounds on the amount of data transmitted by a source node per unit time. Likewise, we study the main characteristics of the proposed techniques. Our experiments reveal that load balancing is achieved amongst the routes and the nodes in the wireless ad hoc network without violating any of the energy constraints, and while adhering to a pre-computed deterministic minimum system lifetime.

In this paper, we propose and describe a new distributed reservation protocol for establishing lightpaths in WDM all-optical networks. Distributed control mechanisms are preferred and employed because of their advantages over centralized ones to set up virtual channels. The new protocol is a combination of the conservative and aggressive backward reservation protocols, which attempts to improve performance by adapting a reservation to network circumstances. On the one hand, the new protocol uses network circumstances and decides and applies a more conservative or aggressive approach. In other words, the protocol progressively fluctuates between those reservation protocols in order to capture their respective advantages. As a result, in extreme cases it acts exactly like either the conservative or the the aggressive reservation protocol. On the other hand, it considers the characteristics of a network to set a retry-list size. As a result, a retry-list size is not determined by a fixed number but modified based on the multiplexing degree of a network, which prevents imposing ineffective retries on a network with a small number of wavelengths and instead encourages more retries for a network with numerous channels. Therefore, the proposed protocol transforms the static nature of existing reservation protocols into a more adaptive one in order to enhance network performance.

When the control and data planes are physically separate, it is important to maintain the established connections in the data plane even if the protocol plane fails. Channel status is maintained by a signalling protocol. Channel status information will be permanently lost as a result of a failure in the control plane having no recovery capability of the constrained-based routing label distribution protocol (CR-LDP). A recovery mechanism for channel status information is proposed in this paper. A downstream node stores a label information database (LID) of assignable (free) labels for each incoming link. A copy of the LID redundantly stored in the upstream node as a label information mirror (LIM). Each LIM and the corresponding LID are synchronised. The recovery of channel status information is guaranteed.

One of the key issues in QoS provisioning in high-speed networks is how to determine a feasible route that satisfies the given QOS requirements while efficiently utilizing network resources. In this paper, we study the NP-complete problem of path selection subject to multiple constraints and propose a heuristic solution, which essentially divides an entire QoS-path into at most two "superedges" that is connected by a "relay node". A superedge is defined as a connected segment of the path on which all routers use the same routing metric for packet forwarding. The node connecting the two superedges is called relay node. This property makes the heuristic be able to support stateless forwarding, i.e., no flow-specific state information is required to maintained at intermediated nodes on a QoS routing protocol. Its computational complexity is deduced to be 0(m|V/sup 2/|), where m, a very small integer, is the number of the concerned QoS metrics and |V| is the number of nodes in network. Simulation results show that the heuristic can achieve near optimal performance.

Contrary to present conjectures, our medium access control (MAC) based performance studies revealed that battery capacity may not be used as the sole means for achieving energy-based fairness and system longevity for wireless mobile multi-hop ad hoc and sensor networks. Moreover, energy conservation may be attained only if valuable MAC (and PHY) input is passed to the network layer. Hence, we propose two schemes, the objective of which is to enhance the operation of existing power-based multi-path routing protocols via cross-layer designs and optimal load assignments. Our proposed schemes, namely, energy-constrained path selection (ECPS) and energy-efficient load assignment (E2LA), employ probabilistic dynamic programming techniques and utilize cross-layer interactions between the network and MAC layers. To the best of the authors' knowledge, this is the first time that MAC-originated information is used as the basis for achieving energy-efficient routing.

We introduce the virtual base station on-demand (VBS-O) routing protocol for wireless mobile ad hoc communications, which built on top of any mobile infrastructure protocol, the warning energy aware clusterhead (WEAC) infrastructure protocol. The WEAC protocol establishes a dynamic wireless mobile infrastructure to mimic the operation of the fixed infrastructure in cellular networks. In the WEAC protocol, a mobile station is elected from a set of nominees, based on its energy level, to act as a temporary base station within its zone. Mobile stations elected as VBSs are used to track other mobile stations in the ad hoc network. The VBS-O routing algorithm utilizes the mobility-tracking mechanism of the WEAC infrastructure creation protocol to route the packets. The VBS-O architecture complying with QoS guarantees imposes the use of a MAC method that guarantees the successful transmission of packets under high mobility and/or heavy load circumstances, and hence meets the QoS constraints dictated by the communications application.

This paper provides an approximate optimal routing algorithm, called relax-converter-first (RCF), for dynamic WDM networks with heterogeneous and partial wavelength conversion capability in each node. The algorithm can derive an optimal solution if the cost of consuming a wavelength converter is set much smaller than is the case for taking a wavelength channel. We propose a wavelength graph technique along with a modified Dijkstra's shortest path first algorithm. Simulation is conducted to verify the performance in terms of blocking probability focusing on the following two themes: first, a comparison in performance is conducted among the cases of using fixed alternate routing, shortest path first algorithm with wavelength graph (SPAWG), and RCF; second, the performance of using the RCF scheme is examined with different cost of taking a wavelength converter in network nodes with different wavelength conversion capability. We also provide the simulation statistics about the optimality in using the RCF scheme under different network environments.

In previous work, we thoroughly studied the intricate problem of energy conservation in wireless ad hoc networks. Consequently, we proposed a novel framework, namely quasi-guaranteed system lifetime (Q-GSL), which allows the admission of flows without jeopardized the limited energy of the wireless stations. A noteworthy feature of Q-GSL is that it provides a means for contention mitigation and load balancing. The upper bound on the packet rate is computed in the absence of the energy overheads associated with routing, contention resolution, channel sensing, etc. The results reported herein augment our previous conclusions about the usefulness of the proposed framework. We show that load balancing is achieved amongst the routes and the nodes in the wireless ad hoc network without violating any of the energy constraints, and while adhering to a pre-computed deterministic minimum system lifetime.

In this paper, we propose a novel cluster-based infrastructure creation protocol, namely: warning energy aware clusterhead (WEAC). WEAC establishes a dynamic wireless mobile infrastructure. As in all cluster-based infrastructure protocols, in the WEAC protocol, a mobile node is elected from a set of nominees to act as a temporary base station for a period of time within its zone. We study the characteristics and performance of the WEAC protocol by means of simulation. It is shown that the WEAC protocol scales well to large networks of mobile stations, and it outperforms other routing energy saving amongst the network. The WEAC protocol would facilitate the development of a comprehensive and promising framework for quality of service (QoS) management in wireless mobile ad hoc networks once the proper integration of the MAC protocol with the routing and call admission control mechanisms is established. At that time, it would lay the groundwork for assigning bandwidth, and/or implementing priorities, and hence for QoS-based routing by conveying the quality of a path prior to call setup.

Assured service has been proposed within the differentiated services (DiffServ) model to provide relative service differentiation by attempting to allocate bandwidth to different users in a controlled way during periods of network congestion. In this paper, we analyze the assured service scheme by means of a priority queueing system with state-dependent service scheduling based on thresholds. We consider the case of two classes of priority, carry out a mathematical analysis and numerically obtain the average delay endured by packets in each priority class and the loss probability for each class. To quantify the gain obtained under our threshold-based priority scheme over static priority based schemes, we also study the priority scheduling and weighted fair queuing models, and compared our results with the ones obtained using these two models.

This paper proposes a scalable design for next-generation optical cross-connects (OXCs). We present a novel strategy for dimensioning the switching capability as a long term planning. Switching fabrics in OXCs have to be expanded according to traffic growth, which may incur a scalability problem due to the exponentially increasing cost in manufacturing and maintenance. The proposed scheme expands the switching capacity of OXCs with waveband- and fiber-switching components (or, equivalently, expands the network capacity with waveband- and fiber-switching tiers). To minimize the number of extra fibers for waveband- and fiber-switching tiers required to satisfy a given traffic matrix, we formulate the problem of routing and wavelength assignment (RWA) with tunnel allocation (RWAT) into a constraint programming (CP) process. The CP is simplified as two integer linear programming (ILP) processes that are performed sequentially. Experiments are conducted on four examples to compare the throughput and the number of switching points when different switching architectures are adopted under different traffic increase. The benefits of our approach are demonstrated. Finally, we conclude that the proposed optimization scheme can dimension the networks with expandability and scalability to the growing traffic demand.

We solve the problem of protection domain allocation in dynamic WDM networks under the framework of short leap shared protection (SLSP). A novel survivable routing algorithm, namely dynamic SLSP (D-SLSP), is proposed, which contains two on-line algorithms: heavy fixed alternate routing (H-FAR) and cascaded diverse routing (CDR). A novel approach for deriving the link-state for solving the optimal protection path corresponding to a working path is given. A simulation is conducted using four different networks (22-, 30-, 79-, 100-node) for a comparative study between the ordinary shared protection schemes and the SLSP. Simulation results show that the best efficiency is achieved by using SLSP with a properly chosen diameter in each protection domain for every connection request, according to the size and topology of the network.

A novel planning algorithm, namely capacity-balanced alternate routing (C-BAR), is proposed for enhancing fixed alternate routing in dynamic wavelength-routed WDM networks. With C-BAR, alternate paths between each source-destination (S-D) pair are defined at the network planning stage according to the load distribution and the location of each S-D pair, so that the routing of lightpaths can take the most advantages of the load-balancing characteristic of the alternate paths. A methodology for designing the number of alternate paths between an S-D pair for achieving a specific performance requirement is demonstrated. Simulation is conducted to examine the proposed approaches, and show that the C-BAR algorithm can significantly improve the performance in blocking probability compared with the other reported RWA schemes.

The intricate problem of energy conservation in wireless ad hoc networks is of great significance due to the limited battery capacity of the participating mobile devices. However, the simulation studies carried out for table-driven, on-demand, and cluster-based ad hoc routing protocols fall short of examining essential power-based performance metrics, such as average node and network lifetime, energy-based protocol fairness, average dissipated energy per protocol, and standard deviation of the energy dissipated by each individual node. In this paper, we present a thorough energy-based performance study of power-aware routing schemes for wireless mobile ad hoc networks. Our energy consumption model is based on a detailed implementation of the IEEE 802.11 physical layer convergence protocol (PLCP) and medium access control (MAC) sublayers. To our best knowledge, this is the first such detailed performance study. Some implications for power-efficient protocol design In ad hoc wireless networks are also discussed.

We extend an existing multicast routing protocol, multicast extension to OSPF (MOSPF), to achieve tunnel multicasting. The extension is as follows. Tunneling is introduced for supporting tunnel multicasting, which aims at reducing the protocol overhead associated with MOSPF. Simulation results show that the extension can reduce protocol overhead significantly without affecting the per-destination shortest path characteristics of a resulting tree or introducing any extra control overhead.

This paper studies the virtual topology reconfiguration problem for all-optical wavelength-routed WDM networks. We consider dynamic reconfiguration in response to changing traffic demands and formulate the problem as an Integer Programming problem with multiple optimization objectives, aiming at maximizing the network throughput, minimizing the average propagation delay over a lightpath, and minimizing the reconfiguration cost. We use heuristics to obtain approximate optimal solutions and propose a balanced alternate routing algorithm (BARA) based on a genetic algorithm. To make the problem computational tractable, we assume wavelength converters at each network node and approximately divide the optimization process into two relatively independent stages: route computation and lightpath routing. At the route computing stage, the aim is to compute a set of alternate routes for each pair of source and destination nodes in the network. At the lightpath routing stage, the aim is to decide an "optimal" route for each of the lightpaths between a pair of source and destination nodes from a set of alternate routes, and the decisions are subject to the formulated constraints and optimization objectives. Through simulation experiments, we show the effectiveness of BARA.

GMPLS was devised to be able to support multi-granularity traffic and bundling of wavelength channels in the optical domain. It has been a challenge to achieve an efficient and flexible use of the multi-granularity OXCs (MG-OXCs) in the optical next generation Internet which is assumed to deploy a generalized MPLS (GMPLS) based control plane. In this paper, a heuristic algorithm, capacity-balanced static tunnel allocation (CB-STA), is proposed for solving the problem of routing and wavelength assignment with tunneling (RWAT), which is aimed at facilitating an efficient use of bandwidth in the WDM networks with MG-OXCs. CB-STA allocates fiber and waveband tunnels into networks at the network planning stage, which requires each tunnel to have a fixed length and capacity-balanced characteristics, in order to increase the link utilization in the fiber and waveband switching layers. A comparison is made, using simulation, between CB-STA and a dynamic tunnel allocation scheme. Detailed discussions are provided.

We propose an architecture for provisioning non-disrupted QoS guarantees in mobile ad hoc networks, and extend the scalable resource reservation protocol (SRRP) for signaling in ad hoc networks. In particular, we present a number of techniques that can enable QoS guarantees in ad hoc networks, including geographical reservation and clusterhead election (GRACE), the request-to-reserve/object-to-reserve/clear-to-reserve (ROC) reservation mechanism, and ad-hoc MPLS. We introduce a scalable adaptable reservation architecture (SARA) as a common architecture for reservation in SRRP. SARA is a scheme for signaling, reservation and QoS adaptation in ad hoc mobile wireless networks and which can also be used in the Internet. Finally, we propose geographical subpath protection, geographical circumscribed protection, and geographical extension protection with shared virtual reservation for non-disrupted QoS guarantees in the presence of interference, high mobility, bursty traffic, and/or other faults, without wasting expensive radio resources unnecessarily.

Shortest path tree (SPT) is the most widely-used multicast tree type due to its simplicity and low per-destination cost. An SPT is constructed by the union of the shortest paths from the source node to each destination. However, SPT does not consider overall network resource utilization. We propose a destination-driven shortest path tree algorithm, which aims to construct a low-cost SPT by considering link sharing between different destinations. The computational complexity of the presented algorithm is O(|E|log|V|), where |E| and |V| are the number of edges and nodes in a network respectively. Simulation results are used to demonstrate the high performance of the proposed algorithm.

Advance reservation is a useful network service that can not only provide guaranteed services for real-time applications but also allow networks to better plan their resource allocations. In this paper, we explore advance reservation in optical networks and focus on the design of effective routing and wavelength assignment (RWA) algorithms to support advance reservation service in wavelength-routed WDM networks. We first introduce the advance reservation concept and present an advance reservation model. Based on this reservation model, we study the design of effective RWA algorithms for different types of advance reservation and give some example algorithms. We also discuss related issues involved in supporting the coexistence of advance and immediate reservations. In addition, we briefly review some related work on advance reservation and the underlying RWA problem in wavelength-routed WDM networks.

In the next generation Internet, connection requests will be arriving and departing at high rates with a non-uniform traffic pattern. An appropriate WDM network control scheme must be implemented to set up lightpaths for each request in an efficient manner. Most previous dynamic wavelength routing algorithms were based on accurate link state information. However, maintaining and distributing such information requires complex WDM network control signaling and management overhead. Moreover, the frequent changes in data traffic raise the difficulty of maintaining accurate wavelength availability information. An adaptive alternate routing is proposed for multi-fiber WDM network by using approximate congestion information. Simulation results show that the proposed routing scheme can achieve similar performances to the fixed-paths least-congestion (FPLC) algorithm, but with much less control overhead.

This paper studies the virtual topology design and reconfiguration problem of virtual private networks (VPN) over all-optical WDM networks. We formulate the problem as an integer programming problem with objectives to maximize the network throughput, and to minimize the average end-to-end propagation delay, and to minimize the reconfiguration cost. Load balancing and alternate routing are considered in order to increase the network throughput. A balanced alternate routing algorithm (BARA) is also proposed to obtain approximate optimal solutions to the formulated problem. To make the problem computationally tractable, we assume wavelength converters at network nodes and approximately divide the optimization process into two relatively independent stages: route computing and lightpath routing. To improve the computational efficiency, a genetic algorithm is used in BARA. The effectiveness of BARA is shown through simulation results.

In this paper, we solve the survivable routing problem in dynamic WDM mesh networks under the framework of short leap shared protection (SLSP). A novel algorithm called cascaded diverse routing (CDR) is proposed. We also demonstrate a novel approach to solving the diverse routing problem in networks with dynamic traffic for the purpose of shared protection, called iterative two-step-approach (ITSA). Simulation is conducted using four different networks (22-, 30-, 79-, 100-node) for a comparison between ordinary shared protection schemes and the SLSP scheme. Simulation results show that the best performance can be achieved with well-designed diameter of protection domains for every connection request according to the size and topology of the network.

This paper solves the problem of path selection for connection-oriented MPLS-based mesh networks with a special focus on implementation issues in middle-sized networks, such as metropolitan-area networks (MANs). A novel network planning algorithm, called capacity-balanced alternate routing (C-BAR), is proposed. For C-BAR, alternate paths between each ingress-egress pair are defined at a network planning stage according to the network topology and potential traffic load and location of each ingress-egress pair so that load-balancing can be achieved in routing label switched paths (LSPs). Both analytical and simulation-based studies have been conducted to examine the proposed approach. The results show that the C-BAR algorithm can significantly improve the performance in blocking probability by spreading potential traffic to the whole network compared with other reported connection-oriented routing schemes.

Spare capacity planning is designed to find the minimum amount of spare capacity to be allocated throughout a network so that the network can survive from network component failures. In this paper, the spare capacity planning problem is investigated for long-haul wavelength division multiplexing (WDM) networks. A three-step method is developed for solving the problem. First, heuristic approaches are used to select both candidate working routes and protection routes in order to achieve approximate optimal performance while maintaining a computational feasibility. Second, traffic requests are distributed on the obtained candidate working and protection routes optimally using genetic algorithms (GA). Finally wavelengths are assigned to working lightpaths and shared protection lightpaths. The major advantage of the new approach is the ability to incorporate nonlinear constraints and nonlinear cost functions into the GA, which are introduced by sharing protection links between shared risk link groups (SRLG). Moreover, by considering SRLG constraints in the spare capacity planning phase, wavelengths can be allocated to each shared protection route before failures happen, so that shorter restoration latency can be achieved. Numerical results illustrate that the proposed approach is more cost-effective than the single-path protection method.

In this paper, an efficient and on-the fly infrastructure is created using our proposed mobile point coordinator (MPC) protocol. Based on this protocol, we also develop an efficient MAC protocol, namely MPC-MAC. Our MAC protocol extends the IEEE 802.11 standard for use in multihop wireless ad-hoc networks implementing both the DCF and PCF modes of operation. The goal, and also the challenge, is to achieve QoS delivery and priority access for real-time traffic in ad hoc wireless environments while maintaining backward compatibility with the IEEE 802.11 standard. The performance of MPC-MAC is compared to the IEEE 802.11 DCF-based MAC without MPC. Simulation experiments show that in all cases the use of PCF benefits real-time packets by decreasing the average delay and the discard ratio. However, this may come at the expense of increasing the average delay for non-real-time data. On the other hand, the discard ratio for both real-time and non-real-time packets improves with the use of PCF. Therefore, our MPC-MAC outperforms the standard DCF IEEE 802.11 MAC protocol in multi-hop ad-hoc environments.

Wireless mobile ad hoc stations have limited battery capacity. Hence, ad hoc routing protocols ought to be energy conservative. However, The simulation studies carried out for table-driven and on-demand ad hoc routing protocols fall short of examining essential power-based performance metrics, such as average node and network lifetime, energy-based protocol fairness, average dissipated energy per protocol, and standard deviation of the energy dissipated by each individual node. In this paper, we present a thorough energy-based performance study of power-aware routing protocols for wireless mobile ad hoc networks. Our energy consumption model is based on a detailed implementation of the IEEE 802.11 physical layer convergence protocol (PLCP) and medium access control (MAC) sublayers. To our best knowledge, this is the first such detailed performance study. Moreover, we propose some novel enhancements to routing in wireless ad hoc networks that enables the admission of flows without jeopardizing the limited energy of the wireless stations.

We propose time division multiple access with circular reservation (TDMA/CR), a time/space division multiple access (TSDMA)-based medium access control (MAC) protocol for wireless mobile networks with control units, including wireless LANs, cellular networks with ad hoc relaying capability, and ad hoc networks with access points or clusterheads. Different from the MAC protocol of IEEE 802.11, TDMA/CR is centralized and can utilize the computation capability of base stations or access points to increase network throughput, reduce latency, and provide QoS guarantees. We evaluate the performance of TDMA/CR and show that the utilization achievable by the wireless-tree (or splitting) channel access mechanisms of TDMA/CR is about 40% to 46% and the channel access delay is small and bounded. Moreover, TDMA/CR can achieve considerably higher throughput (e.g., by a factor of about 3 or higher) due to its support for variable-radius transmissions in ad hoc wireless networks.

GMPLS is one of the most promising frameworks proposed for the next generation optical Internet, which supports multi-granularity of switching types including fiber-, waveband- and lambda-switching in the optical domain. We present some algorithms for solving the routing and wavelength/tunnel assignment (RWTA) problem based on the multi-granularity 4-tier switching architecture. We also propose novel network planning algorithms, the weighted network link state, and an enhancement to the fixed-alternative routing scheme, the heavy fixed alternative routing (H-FAR), to facilitate RWTA. We show that with the weighted network link state and H-FAR, the RWTA problem in the optical Internet with multi-granularity OXCs (MG-OXCs) can be solved efficiently, and the performance in terms of call blocking rate in a network with MG-OXCs is comparable with that in a lambda-switched network, which means the link utilization of tunnels is close to that of wavelength-switched channels.

In this paper, we propose a novel infrastructure formation protocol for wireless mobile ad hoc networks. In our proposed protocol, namely, the Power-Aware Virtual Base Stations (PA-VBS) protocol, a mobile node is elected from a set of nominees to act as a base station within its zone based on its residual battery capacity. Likewise, we study the characteristics and performance of PA-VBS by means of simulation. It is shown that PA-VBS outperforms other infrastructure-formation protocols in terms of load balancing, and attains fair clustering. PA-VBS is also shown, in our simulation experiments, to react positively to different routing loads. To the authors' best knowledge, this is the first time that battery capacity has been used as a basis for developing a wireless mobile infrastructure, and achieving load balancing.

QoS routing has generally been addressed in the context of reservation-based network services (e.g. ATM, IntServ), which require explicit (out of band) signaling of reservation requests and maintenance of per-flow state information. It has been recognized that the processing of per-flow state information poses scalability problems, especially at core routers. To remedy this situation, in this paper we introduce an approach for stateless QoS routing in IP networks that assumes no support for signaling or reservation from the network. Simple heuristics are proposed to identify a low-cost delay-constrained path. These heuristics essentially divide the end-to-end path into at most two "superedges" that are connected by a "relay node". Routers that lie on the same superedge use either the cost metric or the delay metric (but not both) to forward the packet. Simulations are presented to evaluate the cost performance of the proposed approach.

This paper studies distributed lightpath control in wavelength-routed WDM networks. We propose to introduce a destination-routing mechanism for lightpath establishment, which uses global network state information for wavelength routing and allows the destination node of a lightpath to decide the route. The purpose is to use the most recent network state information to make a routing decision so that wavelength reservation failures can be minimized. Meanwhile, we also consider connection restoration in the occurrence of a link failure and introduce a destination-initiating mechanism that allows the destination node of a broken connection to initiate a connection restoration process. The purpose is to reduce the connection restoration time so that a backup path can be provisioned rapidly. Based on both mechanisms, we further propose an efficient distributed control protocol for lightpath establishment and restoration. The paper explicitly describes the major procedures of the protocol, discusses its significant properties, and evaluates its performance in terms of the request blocking probability, and the connection setup or restoration time.

In this paper, we investigate the behavior of multiplexed traffic streams of different traffic classes in the radio environment, and study the effect of such behavior on the performance of the on demand TDMA (D-TDMA) MAC protocol. An adaptive polling mechanism, referred to as polling respond-bandwidth reservation algorithm (PR-BRA), is proposed for providing a bounded channel access delay for the active/ready variable bit rate virtual channels (VBR VCs). The performance of PR-BRA is investigated under different traffic load and network conditions, and a general conclusion on the system performance is drawn.

The task of finding a physically disjoint protection path from a working path to guarantee service continuity during the occurrence of failures has been one of the most important issues for improving survivability of the optical Internet. We focus on the study of finding asymmetrically weighted optimal node-disjoint path-pairs for shared protection so that network performance in terms of success rate of building up disjoint path-pairs and average restoration time are improved. We first propose and examine a novel heuristic algorithm to solve the diverse routing problem in a network with heterogeneous link states for working and protection path pairs, which is based on the sub-optimal path-solver (SOPS), a new method for finding loop-less K-shortest paths. A simulation-based study on the weighting parameter of working paths versus network performance is conducted.

Advance reservation is a useful network service that can not only provide guaranteed services for network users but also allow networks to better plan their resource allocations. This paper studies advance reservation for wavelength-routed WDM networks. The focus is primarily on effective routing and wavelength assignment (RWA) solutions to supporting different types of advance reservations as well as the coexistence of both advance and immediate reservations. The paper briefly reviews related work in advance reservation, presents the potential advance reservation problems, and defines an advance reservation model for wavelength-routed WDM networks. Based on this reservation model, we develop effective RWA solutions to supporting different types of advance reservations. We also propose and discuss effective control mechanisms for supporting the coexistence of both advance and immediate reservations.

The integrated services (Intserv) architecture provides the Internet the ability of delivering end-to-end QoS to applications over heterogeneous networks. Existing approaches for providing Intserv require routers to manage per flow states and perform per flow operations. Such a stateful network raises the scalability concerns when the network size or the number of flows is significantly large. The differentiated services (Diffserv) approach proposes a scalable means to deliver IP QoS based on aggregate traffic handling. We present end-to-end QoS guaranteed services over Diffserv network. This is implemented by introducing an sender-initiated resource reservation mechanism over Diffserv. This way we simultaneously achieve scalability and better control on the services. We present a detailed experimental study of the end-to-end QoS behaviour. Our results demonstrate that it is very desirable to implement the reservation mechanism over Diffserv to achieve more flexible and efficient end-to-end guaranteed QoS.

We propose a novel protocol for wireless mobile ad hoc networks, which establishes a dynamic wireless mobile infrastructure. The proposed protocol, namely, the power-aware virtual base stations (PA-VBS) protocol, mimics and maintains the operation of the conventional fixed infrastructure in cellular networks. In the PA-VBS protocol, a mobile node is elected from a set of nominees to act as a temporary base station within its zone based on its normalized power value. Likewise, we study the characteristics and performance of PA-VBS by means of simulation. It is shown that PA-VBS scales well to large networks of mobile stations, and that it outperforms other infrastructure-formation protocols in terms of load balancing.

The LDP (label distribution protocol) is used in the control plane to control an optical network. The data plane and the control plane of an optical network could be physically separate. So a failure in the control plane does not necessarily imply a data plane failure and that user communications have to be interrupted. The standard LDP, however, does not provide any mechanism to recover the knowledge stored in LDP entities about the status of the data plane after the faults are fixed. This is a reliability problem of LDP and results in the unnecessary degradation of user communications. On the other hand, in MPLS-enabled IP networks, being able to recover LDP sessions would be potentially faster and more scalable than to re-establish all affected LSPs. The proposed recovery method of LDP for the control plane failures uses label information mirrors (LIMs) in upstream downstream label switching routers (LSRs). Each LIM is a copy of the label information database (LID) in the LSR of an LDP session. We propose a systematic approach to synchronize the contents of a LIM and the corresponding LID, and show how a LIM is used to handle a control plane failure. Detailed descriptions of the recovery procedure for both control channel failures and control node failures are presented. Some significant features of the proposal are outlined.

We investigate the behavior of multiplexed traffic streams of different traffic classes in the radio environment, and study the effect of such behavior on the performance of the D-TDMA MAC protocol. Based on such traffic behavior, we investigate a traffic/network management set for improving the overall performance of the network.

We present a framework for scalable quality of service networks which would allow the network designer and network manager to cope with the uncertainties of network traffic and services and also at the same time simplify the overall network planning and dimensioning process. Our approach is based on decomposing the network by service and geography. The paper also discusses the role of optics in this framework and challenges that have to be addressed for the realization of such networks.

We propose an approach to design a distributed rate-based traffic controller to flow-regulate the best-effort service (e.g., ABR) traffic and guaranteed service traffic through a high-speed switch. The controller is distributed among the source nodes and has a very simple structure. Its local controller at each source node is open-loop stable and only requires the knowledge of the queue length at the bottleneck switch. We show that the proposed controller is fair and can stabilize the network with long variable delays. This controller does not have oscillation and can achieve high utilization.

This paper presents the performance evaluation of per-hop forwarding behavior in the differentiated services Internet. Both the expedited forwarding and the assured forwarding behaviors are observed and investigated in terms of packet delay and packet drop rate. This investigation was carried out using Queen's University IP Simulator v2.0 (QUIPS-II). A significant amount of results have been obtained under various parameter settings. The results show that the Diffserv per-hop forwarding mechanisms can provide good service differentiation on the Internet.

We thoroughly analyze the performance of the slotted Aloha (S-Aloha) scheme as a channel access method for a hybrid demand assignment TDMA protocol for broadband wireless networks. The performance of such embedded S-Aloha (ES-Aloha) is compared with the normal S-Aloha scheme, as a stand-alone scheme, and some useful results and conclusions are drawn. In addition, the importance of some performance measures for the channel access scheme is identified and their impact on QoS provisioning is defined. Moreover, the effect of call admission control (CAC) in the broadband wireless network performance is discussed and a general conclusion is presented.

Link-state routing protocols are being increasingly used in modern communications networks. A salient feature of this class of routing protocol is that the network connectivity and the state information of all links are available to the nodes for making routing decisions. Two main components of a link-state routing protocol are an update mechanism and a routing algorithm. These components must be properly designed for efficient routing. Various alternatives are possible for each of these components leading to different scenarios for the routing protocol. In this paper, we quantitatively examine the impact of these alternatives on the performance of a sample network supporting a single service class using call-level simulations.

Alternate path routing (APR) can be used to achieve efficient routing in communications networks. We describe several approaches to APR in connection-oriented networks running link-state routing protocol, and evaluate their performance using call-level simulations. We assume source routing paradigm where primary paths for calls are computed only at source nodes. However, depending on the approach, alternate paths can be computed at source, intermediate or even destination nodes. We present simulation results to show that, if not carefully used, APR may degrade network performance under heavy load. Finally, we describe two mechanisms for improving APR, and address some of their implementation issues.

We propose an approach to design a rate-based proportional traffic controller in order to flow-regulate the best-effort service (e.g., ABR traffic) and guaranteed service traffic through an ATM switch. The controller is distributed and it has a very simple structure. Its local controller at each source node is open-loop stable and only requires the knowledge of the buffer occupancy at the bottleneck switch. We show that this controller is fair and is not sensitive to the change of virtual connections (VCs) over time. It does not have oscillations and can achieve a high utilization.

An efficient dynamic routing protocol is necessary for future broadband networks where a variety of services with different characteristics and QoS requirements are integrated. The main components of a dynamic routing protocol are the exchange of topology state information, the routing algorithm and the routing decision. The exchange of topology state information helps in keeping the network nodes updated on the network status and hence making the correct routing decision. The routing algorithm is responsible for computing the best paths for different source-destination pairs. The routing decision taken at a node decides the path to be followed by a certain call. Different alternatives are possible in the design of each of these components leading to different scenarios for the routing protocol. These different scenarios are examined based on both analytical and/or simulation results and the one with the best results in terms of efficiency as well as various performance measures is presented. The simulation is carried out over a practical network topology; the NSFNET.

This paper analyzes and compares the queueing performance of copy networks for multicast ATM switching. Both nonbuffered and input-buffered copy networks are studied. Particularly, the shared-input-buffering approach is investigated, and the performance improvement obtained by employing the buffer in the network is demonstrated. The effectiveness of the dynamic cell splitting scheme is presented as well.

ATM networks support multimedia traffic where diverse services have to be provided and various QoS requirements have to be met. Routing plays an important role in guaranteeing the QoS. However conventional routing will cause a significant overhead when the network size gets very large or rerouting occurs frequently due to the varying link state. The objective of our dynamic routing scheme is to perform more efficient routing over a more effective and simpler topology which is abstracted from the original full topology based on the dynamic link state. Only those links with high probability to satisfy the QoS of the call are included in the effective topology. It is an efficient way to prevent rerouting from occurring too often because the blocking probability over this effective topology is significantly low. A hierarchical routing model is also proposed to further reduce the amount of information that has to be stored and exchanged for routing. We present the simulation results of our dynamic routing scheme along with the hierarchical routing model and its implementation over QUARTS, a simulation testbed for ATM networks.

We describe the static and dynamic channel allocations from a combinatorial point of view which is based on users' point of view and product spaces. In particular, we show the importance of state-position probabilities and their role in the modeling of users with different speed characteristics. We describe two queueing models and the analytical evaluation of the overload probability in the context of channel assignment. The paper is guided by a series of simulation results through which we propose a new channel allocation approach for high speed users in which case the probability of overload is analytically expressed.

We construct an equivalent model of the proposed location update tree structures. In particular, we show that the performance of the queueing model is dependent on the users' population and speed. We analyze two queueing disciplines G/M/1, and G/D/1 explaining the observed phenomena analytically. Finally, we give an analytical reasoning for the observed phenomena.

The gamma network is enhanced to derive a balanced gamma network with the addition of an additional link. The performance of the proposed network is analyzed in comparison with the existing networks. The performance of replicated networks and of networks with one internal buffer are investigated. These networks are studied using two assumptions: the common assumption that each destination can accept only one packet in a given cycle and the assumption that any number of packets can be accepted by a destination. Balanced gamma networks exhibit good performance, enable simple routing schemes, and are modular.>

A performance analysis to compute the packet loss, call blocking, and packet delays of a typical user in an integrated voice-data-video satellite internetworking environment is discussed. The uplink technique used is a hybrid packet/circuit switched approach of the demand assignment type, while the downlink is a time-division-multiplexing (TDM) technique. Onboard the satellite, a baseband nonblocking switch is used to route the packets from input to output ports. Various amounts of input and output buffering as well as priority rules and blocking resolution algorithms are used. The authors conduct a performance analysis for the problems at hand and identify the best ranges for the different parameters involved.>

A constrained Kalman filtering approach for the restoration of images blurred by random point-spread functions (PSFs) is proposed. The effects of the blur model uncertainties are treated as image-dependent correlated noise, and they require the formulation of an augmented-state Kalman filter. Additional a priori image information, including deterministic information, is incorporated into the augmented-state Kalman filter as convex set constraints. Efficient constrained optimization of the augmented-state Kalman gain is achieved by projecting the unconstrained optimal gain onto the convex sets. The proposed constrained filter is useful in cases of image restoration where the degrading PSF is only partially known, such as in the presence of error in blur model parameters.>

A survey of the techniques used in distributed discrete event simulation is presented. Some of the algorithms that have been developed to overcome some of the inherent problems of simulating on distribution systems are then described. The application of distributed discrete event simulation to the performance evaluation of communication networks is addressed. The design and implementation of the DISDESNET (distributed discrete event simulation of networks) simulation package for the simulation of general communication networks is described. Results of tests performed on different configurations are examined and found to demonstrate the flexibility of the package.>

Computer-aided design, analysis, and simulation techniques for communication networks are surveyed. The focus is on analytic and simulation techniques that are either amendable to, or require, implementation on a computer. Issues relating to the implementation of these techniques on a computer as well as their embodiment in software tools are addressed. Past and present work in these areas is surveyed, the application of these techniques to network performance modeling and analysis is discussed, and promising directions for future research are indicated.>

A design tool has been developed in the form of a computer simulation package to aid in the design and performance evaluation of communications controllers with mixed traffic. Such systems are assumed to have the capability of carrying synchronous traffic, asynchronous traffic, or the mixture of both. Multiplexing as well as switching between different types of traffic are among other features provided by these controllers. The hardware/software model is first introduced, and then the computer simulation program is presented along with some results related to the system throughput and delay. A direct application would be in a word processing environment where both inquiry/response as well as file transfer traffic exist.>

The carrier sense multiple access with collision detection (CSMA-CD) protocol cannot be applied directly to radio channels because of the difficulty in sensing remote carrier in the presence of local transmission. Only recently, a new protocol called the CSMA with timesplit collision detection (CSMA-TCD) was introduced to overcome this problem on radio channels. This paper presents an extension of the CSMA-TCD protocol, called CSMA-TCD with multitone tree search (CSMA-TCD-MTTS). In CSMA-TCD, a preamble is transmitted before data transmission. For CSMA-TCD-MTTS, the preamble is modulated with one out ofNtones. In case of a collision, a resolution algorithm splits the terminals involved into anN-degree tree according to the tone chosen. This paper presents the throughput and approximate delay analysis of the CSMA-TCD-MTTS protocol.

Quasi-cut-through is a hybrid switching technique that has been recently proposed for computer networks. This paper deals with the end-to-end static flow control for computer networks using this hybrid switching technique. Two algorithms to handle the retransmissions of erroneous packets over noisy channels are analyzed and compared. Results are presented in terms of maximum user throughput, corresponding network delay, and power.

A general cut-through switching (GCTS) technique is proposed and analyzed. In GCTS, a message may cut through a node if the node becomes free before the message is completely received there. Under the GCTS mechanism, a message may cut through a node even though the node has more than one message in it. This results in minimizing the end-to-end delay time of messages as compared to the other cut-through mechanisms. Moreover, GCTS is more susceptible to exact mathematical treatment.

The design and implementation of a microprocessor-based two-wire full duplex baseband modem is presented. The modem uses the time compression multiplexing technique in implementing a full duplex digital data transmission over a two-wire facility. The line signal used is a baseband bipolar signal. Measurements have been carried out on two prototypes in the lab, and results on the performance of such a modem are reported.

A computer-aided design tool has been developed to study the hardware/software structure of various types of data switching systems used in the local loop distribution of computer communication networks. A simulation package is used to evaluate the performance parameters (such as the system throughput, average message delay, and probability of data loss) of local access systems under different input traffic conditions. Two types of traffic commonly used in teleprocessing applications are considered: the inquiry/response mode and the file transfer mode. Design tradeoffs for a line concentrator and a message interswitch are discussed and their performance is compared. The message interswitch permits a number of low-speed terminals to share communication lines and also to gain access to local common resources such as line printers, databases, and optical character readers.

This correspondence describes an application of COS/MOS integrated circuits in the design of ternary rate-multipliers. The logical implementation of two types of ternary rate-multiplier is described. The first type produces an unevenly spaced output pulse train, while in the second one the output pulses are uniformly spaced. Advantages and disadvantages of the two types are presented.

Ternary storage elements are realized using ternary operators and fundamental circuits, designed with the COS/MOS integrated circuits. Several ternary flip-flops (tri-flops) are constructed and described in detail: the PZN (set positive, set zero, and set negative), the clocked PZN, the D-type, and the T-type. Ternary shift registers and ring counter are formed by means of these tri-flops. A master-slave T-type tri-flop is used for the construction of a ternary up counter able to count from 0 to 3n using the normal ternary code or from -(3n-1)/2 to+(3n -1)/2 when the signed-ternary code is employed. With a small modification, a ternary down counter is also constructed. A divide-by-M ternary counter which can be programmed is described. A memory cell is designed for the construction of a ternary random-access-memory array (TRAM). A ternary decoder and encoder are presented to be the elements of a complete ternary read-only memory (TROM). A modified ternary inverter (MTI) is taken as a unit cell of the ternary memory matrix.