Internet of Things (IoT) devices and edge-platform robots require privacy-aware path planning under strict compute and bandwidth constraints, where continual on-device learning from real-world data is desirable but costly. We propose and evaluateSplit Federated Learning (SFL)–enabledDeep Q-Networks (DQN), termedSFL-DQN, which partitions the Q-network into a lightweight on-device encoder and a shared server-side action–value head with online/target stabilization. Devices keep raw observations local and exchange only intermediate feature representations and their gradients; periodicFederated Averaging (FedAvg)realigns client encoders to mitigate representation drift under heterogeneous, non-independent and identically distributed (non-IID) experience. In grid-world navigation withonemoving obstacle, SFL-DQN matches a non-federated, non-split DQN baseline in episodic return and task success and attainsBreadth-First Search (BFS)–equivalent shortest-path optimality on held-out maps. WithKclients, each device uses only 1/Kof the single-device interaction budget (e.g., 1,000 vs. 4,000 episodes whenK=4), reducing theclient-sidetraining burden by offloading the value-learning head to the server. Split–federated training introduces feature-level communication overhead and does not necessarily reduce system-wide energy under all network conditions; instead, SFL-DQN enables a practical edge–cloud learning loop without raw-data aggregation.

Remote direct memory access (RDMA) is widely deployed in production data centers to enable low-latency transmission. The current multipath RDMA transmission protocols effectively improve link utilization by allocating traffic to equal-cost parallel paths. To address packet reordering, they struggle to control the level of out-of-order packets by using bitmaps. However, under asymmetric path status and highly dynamic traffic scenarios, a large number of out-of-order packets easily cause bitmap overflow and frequent unnecessary retransmission, resulting in goodput far below throughput. Motivated by this, we present MPTR, an efficient multipath transport with robust reordering for RDMA networks. At its core, MPTR continuously monitors the multipath congestion status at the receiver and distributes the traffic in a congestion-aware manner to proactively reduce the degree of out-of-order and avoid triggering retransmission due to bitmap cache overflow. The NS-3 simulation results show that MPTR effectively reduces unnecessary retransmission and improves goodput under realistic workloads by up to 34%, 49%, and 51% compared to multi-path remote direct memory access (MP-RDMA), ConWeave, and data center quantized congestion notification (DCQCN), respectively.

Vehicular Ad-Hoc Networks (VANETs) are essential for enhancing traffic management and road safety through vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication. Accurately predicting vehicle trajectories is critical yet challenging in dynamic traffic conditions. The paper proposes an optimized hybrid deep learning model combining Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks to improve trajectory prediction. Simulation results on real-world datasets (GPS tracks of vehicles on highways and in urban areas) demonstrate higher prediction accuracy and efficiency, making the model highly effective for deployment in real-time smart city systems.

As energy concerns grow with the rise of energy-constrained devices, it becomes imperative to design an energy-efficient and adaptive multiple access (MA) scheme, supported with accurate energy efficiency (EE) evaluation. Non-orthogonal multiple access (NOMA) enhances EE, yet downlink NOMA faces challenges in terms of computational complexity and power demands of successive interference cancellation (SIC), problematic particularly for energy-limited devices. Existing studies overlook the additional SIC power consumption at NOMA receivers, thus overestimating EE, and giving misleading insights for real system design. Besides the need for more accurate EE evaluation, an adaptive MA approach based on this additional power consumption is required. This paper proposes a SIC-power-aware adaptive SDMA/cooperative NOMA system. An optimization problem is formulated by optimizing MA mode decision, BS beamforming, power allocation factors, and strong user relaying power, to maximize the system EE. We decouple the problem into SDMA/NOMA selection and power allocation sub-problems, solved via a modified semi-orthogonal user selection (SUS) algorithm, successive convex approximation (SCA), difference-of-convex (DC) programming, and semidefinite programming (SDP) approaches. Numerical evaluation confirms the efficiency of the proposed scheme, compared to the baseline schemes.

Recently, the rapid expansion of the Internet of Things (IoT) has opened up new possibilities and introduced significant security challenges. This evolution enhances everyday life but also increases risks in various domestic and industrial contexts due to growing threats such as cyberattacks and intrusions. To protect both domestic activities and industrial infrastructures, it is imperative to address these challenges. This study enhances security in IoT and IIoT by exploring machine learning-based intrusion detection techniques. The primary goal is to strengthen system protection and ensure the continuity of essential operations. Utilizing the N-BaIoT dataset, designed to simulate realistic IoT attack scenarios, we evaluated the effectiveness of various multiclass classification methods, including PCA dimensionality reduction. After extensive data preprocessing and the application of several classifiers such as KNN, Random Forest, Naive Bayes, Decision Tree, Extra Trees, and XGBoost, we built an effective IoT IDS. The Extra Trees algorithm, in combination with PCA, showed the best performance, achieving an impressive 99.94% accuracy. This underscores the effectiveness of machine learning in detecting and mitigating IoT and IIoT cyber threats and highlights the importance of selecting appropriate methods for optimal results in complex security environments.

Resilient routing within low-power and lossy networks is essential to ensure the continuous and reliable operation of IoT devices. Standard RPL may struggle to adapt quickly and effectively to rapid changes in network conditions, such as link quality fluctuations, link failures, and varying traffic patterns, leading to suboptimal routing decisions, which can affect the QoS. In addition, IoT applications may express different QoS requirements that should be integrated within the routing decision. In this paper, we introduce a new extension of RPL, called Adaptive QoS-RPL, which can effectively adapt to changes in network conditions and node QoS requirements when building the DODAG. The experiments conducted using COOJA reported results that demonstrate the effectiveness of our solution compared to similar protocols.

Existing performance analyses and transmission policy designs under Time-Sensitive Networking (TSN) typically assume that all data flows are periodic and deterministic. However, in real-world scenarios, various sources of uncertainty - such as device failures, environmental variations, or upstream congestion - can lead to unexpected packet arrivals or losses, introducing non-deterministic behaviors into the network. This work develops a stochastic model based on Markov Decision Process (MDP) to capture the dynamics of TSN switch transmission under such conditions. To address the inefficiency caused by stale packets blocking fresher and more valuable ones, we propose a stale packet skipping policy to enhance the transmission efficiency. Specifically, a stale packet is discarded if a newer packet of the same flow is injected into the queue or if its deadline can no longer be met. This paper presents a detailed model description of the stochastic packet behaviors, the transmission system, and the stale packet skipping policy.

With the rapid expansion of smart cities, Intelligent Transportation Systems (ITS) are assuming an increasingly pivotal role. Among the multitude of tasks within ITS, traffic state forecasting stands out. As city boundaries grow, traffic forecasting encounters scalability and network transmission challenges. This research contributes to traffic state forecasting within large-scale, massive Internet of Things (IoT) scenarios. By investigating an urban expressway managing architecture that employs LoRaWAN communication, a novel deep learning-based model named Time Alignment based Temporal-Graph Attention Network (TATGaN) is proposed. Using the temporal-graph attention mechanism, TATGaN is able to extract temporal-spatial information and predict traffic state accurately. Moreover, the time alignment block makes TATGaN capable of handling irregular sequences given by the asynchronous arrival of packets. Simulation results based on OSM data of a specific region within Abu Dhabi show that TATGaN outperforms existing baseline methods in prediction performance with lower error and the higher reliability. Furthermore, the performance evaluation demonstrates the suitability of TATGaN for large-scale traffic network scenarios, attributing its efficiency to the transmission schedule and parameter mechanisms in LoRaWAN networks.

Addressing the limitations of traditional sensor-based systems vulnerable to environmental constraints and trust issues, this article introduces a blockchain-assisted maximum evacuation framework in zero trust hiking trail and mountainous terrain using Internet of Things (IoT) devices that leverages blockchain technology for enhanced security and reliability. We devise three innovative algorithms that are designed to maximize the activation of evacuation nodes, ensuring rapid and efficient disaster response. By updating safe areas and evacuation routes dynamically in real-time IoT environment, the developed algorithms aim to significantly improve emergency response capabilities in challenging terrains. Also, the extensive simulations are achieved to demonstrate the performances of the proposed schemes with discussions for obtained outcomes.

Improving urban mobility management has become increasingly challenging due to the rapid growth in both population and vehicular traffic, impacting the fluidity of mobility and leading to traffic congestion, delays, economic burdens, and adverse effects on public health. Moreover, there are significant concerns regarding air pollution, road accidents, and greenhouse gas emissions associated with this trend. Addressing these issues requires comprehensive strategies that prioritize sustainable transportation modes and urban planning to enhance efficiency and mitigate the negative impacts of mobility on the environment and public well-being. To address these challenges, cities must develop innovative strategies that integrate predictive models into their urban mobility planning. This paper presents a novel approach to predicting trajectories in Vehicular Ad hoc Networks (VANETs). Our proposed architecture leverages recurrent neural networks (RNNs) particularly long short-term memory (LSTM) to capture essential spatial features and temporal dependencies inherent in historical trajectories. Numerical results show that the proposed solution is efficient in terms of prediction.

The emergence of Software-defined Networks (SDN) has played a significant role in shaping the future of networking technologies. SDN aims to improve the flexibility, efficiency, and scalability of traditional networks by centralizing network control, allowing network administrators to manage and control the network through software applications. However, the flexibility provided by SDN architecture unveils numerous emerging network security concerns that require more attention to enhance SDN network security. So, in this paper, we propose a innovative intrusion detection system (IDS) for SDN using a hybrid model that combines CNN-BiLSTM and Transformer Encoder. The proposed approach was tested using the NSL-KDD and CICIDS2017 datasets, achieving accuracy rates of 99.7% and 99.68% respectively. The obtained results demonstrate that our proposed deep learning-based approach provides a robust security solution for detecting intrusions in SDN environments.

In recent years, many research works have focused on RPL, especially in relation to the Internet of Things. This makes RPL an ideal data collection protocol for lossy environments where nodes have low energy levels and limited capabilities. In practice, RPL builds a tree-like topology, often represented by a destination-oriented directed acyclic graph that aims to transmit data to an LLN border router. Many multimetric extensions of RPL are based on a set of predefined metrics and an objective function; each node involved in the topology construction process goes through a parent selection by considering static weights for the set of metrics. The topology is periodically rebuilt to maintain the network while considering the same tools. To provide more flexibility, we present in this paper AOF-RPL, an extension of RPL which is designed to adjust the relevance of each metric based on the network's global condition and QoS requirements of the running applications. The problem is formulated using an MCDM method called ISOCOV. Simulations performed on COOJA show that our approach improves globally the performances compared to similar protocols while enhancing the network lifetime.

The recent study on security surveillance is expanding into numerous research branches and applicable industrial areas for smart devices, mobile robots, drones, autonomous vehicles, internet of things components with a consideration of energy-efficient requirements and environmental features. Also, it is highly necessary to proceed the study of how to build and manage disaster prevention system in complex regions according to eco-friendly services and reliable constructions of relevant infrastructures with communications. In this paper, we introduce a harmonized all-ways security surveillance and disaster prevention system in eco-cities that supports mixed groups of high performance devices with high capability and low performance components with limited resource. The proposed framework provides all-ways surveillance by vertical, horizontal, reinforced crossing shaped formations. With a formal representation, the main research problem of maximizing the extended line for all-ways mixture surveillance and disaster prevention detection is defined with integer linear programming formulation. To resolve the research problem, we devise novel algorithms with initialization as well as demonstrate their performances based on numerical outcomes through various simulations.

Recent vehicle cooperation is utilized for advanced missions, including next-generation communication and dynamic real-time information. active safety control for interconnected vehicles, collection of a heavy traffic information. In particular, the urban traffic surveillance should be one promising topic toward advanced vehicle road cooperation service supported by smart camera and Internet of Things (IoT). In this article, we introduce an augmented fluid surveillance system to create an adaptive fluid surveillance using a group of single lens cameras for intelligent transportation service. The research problem for augmented fluid surveillance is formally defined. Its objective is to optimize the surveillance efficiency for various traffic circumstances of traffic volumes so that the optimal deployment of smart camera is achieved. To settle the problem, two different methods are proposed with clear execution procedures and specifications. Then, their performances are evaluated with obtained results by extensive simulations for diverse settings and applicable scenarios. Furthermore, future research issues and works are described briefly.

The non-adaptive management of traffic lights has proven inefficient for a number of drawbacks. They mainly impinge on CO2 emissions, fuel consumption, traffic waiting time, and heavy traffic. In this study, we propose a traffic signal control system that combines the accuracy of mathematical modeling with the real-time and adaptation features of deep learning (DL) by basing the DL configuration on a mathematical model of the interaction between the environment and the intersection as a Markov decision process (MDP) while taking structural and safety issues into consideration. As a resolution method, we suggest in this study a policy iteration (PI) method, which gives the best policy to follow so as to choose the action that determines the phase duration. These phases minimize the reward, which is the average waiting time (AWT) for all vehicles crossing the intersection. The PI has demonstrated greater efficiency compared to management systems based on fixed durations in various traffic situations. Instead of triggering the PI system for each new situation encountered and minimizing the processing time, the PI will act as a learning method for the DL program. We build a learning database by storing several situations represented by the variables: input flow, latest switching dates, output flows, traffic light states, and queue lengths, with their respective solutions returned by PI as the policy for selecting next switching dates. Due to this configuration, DL has been able to respond optimally and in real-time to different levels of throughput: low, medium, and high.

LoRaWAN (Long Range Wide Area Network) has garnered significant attention within the Internet of Things (IoT) due to its ability to establish a wireless network with massive devices over long distances while minimizing energy consumption. Our previous work shows its suitability for Intelligent Transportation Systems (ITS) scenarios. However, the utilization of the Aloha MAC protocol presents a challenge for LoRaWAN as it grapples with the presence of compromised nodes. These nodes may engage in greedy behaviors, disregarding network regulations to enhance their own performance or acquire additional network resources, and are often difficult to detect. This research contributes to machine learning-based greedy behavior detection methods. After proposing several end-to-end (E2E) methods with different ML algorithms, EDLoG (Encoder-based detection method of LoRaWAN Greedy behaviors) is proposed. It is a greedy behavior detection method combining a Multilayer Perceptron (MLP) encoder network and a statistical abnormal detection algorithm. The performance evaluations are conducted using simulation data under different scenarios given by MELoNS, a Modular and Extendable Simulator for the LoRaWAN Network developed in our previous work. The results show that the proposed method gives a detection recall 15%-20% higher than the baseline method by keeping a high detection precision. Moreover, the proposed methods show high timing efficiency with a running time much smaller than LoRaWAN’s time scale, making the method easily deployed to a real LoRaWAN network.

With the rapid growth of smart cities, Intelligent Transportation Systems (ITS) are playing an increasingly important role. However, with the rapid expansion of city boundaries, ITS faces scalability and energy consumption challenges. The wide range and the massive number of nodes have become significant issues for network technology in ITS. This study proposes an urban expressway managing architecture using LoRaWAN and edge computing. The traffic network is divided into different sections. A LoRa WAN network is established for monitoring and controlling each section by exploiting its low-power, long-range characteristics. Moreover, an edge computing-based traffic state encoder model has been proposed to handle the large amount of data generated by the massive number of nodes. The architecture's procedure allocates tasks to LoRaWAN devices by exploiting their different computing capabilities. Simulation results on real maps of both Abu Dhabi and Beijing demonstrate the high performance and scalability of the architecture. Numerical results also show that the encoder model can effectively reduce network packet size by extracting data features.

LoRaWAN is a network technology that provides a long-range wireless network at low energy consumption. In order to save energy, it takes the pure Aloha MAC protocol and the duty-cycle limitation at both uplink and downlink on the MAC layer. Moreover, LoRaWAN also adapts the orthogonal parameters to avoid the collision. However, the star-topology synchronization and the complicated collision mechanism make quantitative model analysis difficult in LoRaWAN. This study modeled the Class-A device in the LoRaWAN protocol using Probabilistic Timed Automata (PTA). It is a mathematical model that presents the nondeterministic and probabilistic choice with time passing. Using the time representation in PTA, the transmission schedule of LoRaWAN's MAC layer of is modeled. Moreover, the full collision model is built in the PTA. Several properties are verified with the probabilistic model checker PRISM, and the quantitative properties are calculated under different cases.

Non-orthogonal multiple access technique (NOMA) has appeared at the forefront as a viable solution capable of improving spectral and energy efficiency in fifth-generation (5G) and beyond-5G networks. This study aims at evaluating the benefits of adopting network slicing in cooperative NOMA-based systems with underlay Device-to-Device (D2D) communications. We formulate an optimization problem that maximizes the overall system's throughput while guaranteeing slices' technical requirements. We decouple the problem into two sub-problems: first, assigning the cellular users to resource blocks allocated to each NOMA group and then assigning D2D pairs to NOMA groups. A two-stage resource allocation solution by swapping-based matching theory is implemented. Numerical results show that the proposed scenario outperforms other ones in terms of the overall system's throughput and the number of admitted D2D pairs.

LoRaWAN (Long Range Wide Area Network) is rapidly gaining attention in the Internet of Things (IoT) due to its ability to provide a long-range wireless network at low energy consumption. However, with the Aloha MAC protocol, LoRaWAN faces the challenge of malicious behaviors from compromised nodes. Compromised nodes can take greedy behaviors by breaking network rules to improve their performance or obtain more network resources. This study proposes and investigates different greedy behaviors of infected nodes in LoRaWAN on the MAC layer. A straightforward double judgment detection method is proposed. The simulation results show that although the MAC layer of LoRaWAN is robust and resilient against greedy behavior by design, it can still be negatively affected by high-intensity greedy behavior. Moreover, the simulation results also show the high performance of the proposed detection method in different greedy behavior scenarios.

A resource-constrained unmanned aerial vehicle (UAV) can be used as a flying LoRa gateway (GW) to move inside the target area for efficient data collection and LoRa resource management. In this work, we propose deep reinforcement learning (DRL) to optimize the energy efficiency (EE) in wireless LoRa networks composed of LoRa end devices (EDs) and a flying GW to extend the network lifetime. The trained DRL agent can efficiently allocate the spreading factors (SFs) and transmission powers (TPs) to EDs while considering the air-to-ground wireless link and the availability of SFs. In addition, we allow the flying GW to adjust its optimal policy onboard and perform online resource allocation. This is accomplished through retraining the DRL agent using reduced action space. Simulation results demonstrate that our proposed DRL-based online resource allocation scheme can achieve higher EE in LoRa networks over three benchmark schemes.

Mobility management is crucial for urban planning, and accurate road condition information is necessary for safe and efficient transportation. In the context of this study, mobility refers to the quality of the road and the level of service provided to road users. To this end and to advance the state-of-the-art in improving mobility management strategies, we propose a new capability for our ongoing work on the Decentralized Road Traffic Monitoring (DRTM) system: road conditions assessment, aimed at enhancing mobility management for Abu Dhabi city. Our DRTM system uses smartphone cameras, Vehicular Adhoc Networks (VANETs) on vehicle-to-vehicle (V2V) mode, and federated learning to extract and classify road features, such as potholes, cracks, and accidents, impacting overall mobility. The system comprises a smartphone app and a decentralized network of participants, providing real-time insights about road conditions. Our experimental results demonstrate the system’s effectiveness in providing precise and up-to-date information about road conditions, with increased scalability and efficiency compared to centralized methods. By utilizing federated learning, the system ensures data security and privacy.

LoRaWAN (LOng RAnge radio Wide Area Network) is rapidly gaining attention with its capacity for a large devices number, long-range, and low power consumption. Many research works are carried out to evaluate or improve LoRaWAN’s performance in different application scenarios. However, because of a large number of connected devices and a complex environment, it is sometimes impractical to validate the studies with real test-bed or analytical methods. Therefore, the development of accurate network simulators is needed. More-over, extendability and flexibility are invaluable for a simulator to evaluate network performance in different scenarios and studies under a unified environment. To that end, this work presents MELoNS, a modular, extendable LoRaWAN simulator. By representing complete LoRaWAN transmission procedures at the different layers, MELoNS is suitable for the simulation of LoRaWAN in any scenario. MELoNS is lightweight and modular. The independence of network components gives MELoNS a high degree of freedom. Making MELoNS easy to implement and extend for different studies in the same environment. An example application of an intelligent traffic monitoring network is given to show the features of MeLONS.

As the world becomes increasingly interconnected, vehicles are also becoming an integral part of this networked ecosystem. The study of Vehicular Ad Hoc Networks (VANETs) is critical for ensuring the seamless integration of vehicles into the wider network. To achieve this, it is essential to understand the vehicular mobility and infrastructure and for this purpose, multiple simulation tools have been developed to model vehicle traffic. This study presents the key findings of a basic mobility model that has been developed using Matlab and provides a user-friendly Simulink library to model vehicle traffic. The implementation of this model will help researchers and engineers to analyze and evaluate the performance of VANETs, leading to improvements in their overall efficiency and reliability. The model takes into account various parameters, such as road conditions, traffic density, and vehicle speed to generate realistic simulations of vehicle traffic, making it an ideal tool for various applications in the field of vehicular networking. In addition to its ease of use, the mobility model is highly customizable, allowing users to make changes to the parameters and configurations to meet their specific requirements. This makes it a valuable tool for testing new communication protocols, evaluating the impact of different road designs on traffic flow, and much more. An example and simulation results are presented for a specific case study in Abu Dhabi city.

In this paper, we propose a model for Delay Tolerant Networks (DTNs) based coalition and stable structure of all relay nodes to deliver a complete message from one source to one destination using the Epidemic Forwarding Policy. The message is viewed as a series of uniformly sized chunks that are produced by a fixed source. For a message to be considered successfully delivered, all of its chunks must arrive at the fixed destination within the validated time. The Age of Information (AoI) provides a deadline by which all message chunks must reach the destination to be considered timely. Mobile relays within the network will facilitate the transfer of chunks using an insensitive reward mechanism. We propose a distributed coalition algorithm that aims to establish a state of stability among all participating relays in the game. Through this algorithm, we were able to determine that the formation of stable coalitions results in higher payoffs for relay nodes compared to acting alone, as shown in our performance evaluation results.

The foundation of urban traffic management lies in the effective control of intersections with traffic lights. Despite this, the lack of adaptive management strategies in response to changes in traffic patterns results in significant and frustrating delays for motorists. This paper proposes the use of a Markov Decision Process (MDP) to decrease waiting times at intersections. The MDP considers the network environment, encompassing limitations related to both its configuration and protection.Several studies have tackled this issue by examining each intersection in isolation, disregarding its interactions with other intersections. In contrast, the current study takes a systemic approach to the network of intersections. It adopts a non linear approach that takes into account the interconnection between interjections. The highest number of intersections managed in previous studies is eight while it is nine in the model proposed in this study. Given that the Policy Iteration (PI) method is well-suited to the proposed MDP, it has been selected as the resolution method. The PI method, compared to systems with fixed phase durations, has effectively reduced the average waiting time up to 30% compared to non-adaptive systems.

In today’s urbanized world, cities are grappling with new challenges arising from population growth and rapid urbanization. Among these challenges, mobility stands out as a significant concern, as many cities were not initially designed to accommodate the surge in population. Enhancing mobility within smart cities has become a crucial endeavor in order to mitigate traffic congestion and promote sustainability by reducing greenhouse gas emissions. Additionally, improving mobility in smart cities contributes to enhancing the overall quality of life for citizens. Addressing vehicle behavior is crucial in reducing traffic congestion and improving commuting efficiency. Despite having robust infrastructures, disruptive driving habits such as aggressive driving, improper lane usage, and non-compliance with traffic rules can hinder the flow of traffic. By promoting responsible and considerate driving practices, we can optimize traffic flow and create a more efficient and stress-free commuting experience for individuals. Understanding the dynamics of mobility on highways is crucial for identifying the causes of traffic congestion. By analyzing these patterns, valuable insights can be gained, leading to the development of effective solutions for improving traffic flow. This study aims to investigate these aspects and propose strategies to contribute to overall mobility enhancements. To achieve this goal, a novel stochastic model based on the product form that accurately represents overtaking behaviors on highways is presented in this study. The model offers valuable insights into the dynamics of overtaking and provides a comprehensive understanding of this critical aspect of highway traffic. The paper presents a detailed model description and numerical resolution to calculate rewards such as delays and congestion.

In recent years, deep learning techniques have been employed within Intelligent Transportation Systems (ITS) to outperform classical trajectory prediction models, aiming for greater precision and efficiency. Federated learning (FL) has attracted substantial attention for its ability to safeguard sensitive vehicle data while reducing communication overhead. However, FL-based trajectory prediction models face a prioritization dilemma. Some prioritize security, leading to longer computation times and higher resource consumption, while others trade off data privacy for increased accuracy, incurring additional computational costs. In this study, we introduce an approach named FedVANET-TP for predicting trajectories in Vehicular Ad hoc Networks (VANETs). Our method ensures a balanced utilization of computational resources, attains high accuracy and offers optimal privacy. The model is constructed within a FL framework and utilizes an encoder-decoder architecture. This architecture incorporates Convolutional Neural Network (CNN) layers to capture crucial spatial features and Long Short-Term Memory (LSTM) layers for capturing temporal dependencies from historical trajectories. FedVANET-TP has been trained and validated using the NGSIM US-101 dataset. The simulation results show that the model’s average root mean squared error (RMSE) and average overall accuracy are superior to those of the comparison models. This model offers higher accuracy than centralized benchmarks and lower resource consumption than federated-based benchmarks, all while ensuring optimal data confidentiality.

LoRaWAN attracted lots of attention with its capacity for large device numbers, long-range, and low-power consumption. In order to simplify the transmission procedure, a pure Aloha protocol is implemented into its MAC layer. However, as the number of connected devices to the base station increases, the devices’ transmission parameters allocation becomes a vital issue related to network performance. This research contributes to the decentralized dynamic spreading factor (SF) allocation strategies during transmission by proposing a score table-based evaluation and parameters surfing (STEPS) approach. STEPS is a reinforcement learning-based method that evaluates and changes the parameters based on probability and score tables. It provides a nondeterministic parameter selection method by updating the table while transmitting. Some variants of STEPS with different algorithms are proposed. Moreover, an estimation-based initialization is proposed to improve learning performance. Simulations and statistical tests are carried out with MULANE, a lightweight LoRaWAN Simulator developed in our previous work. The results show that the estimation has a high confidence level. Compared with the baseline methods, the proposed methods reduce energy consumption by 24%–27% in different numbers of nodes. For bi-directional transmission, the proposed methods increase the 18% network throughput in a small number of nodes and 33% in a large number of nodes. Moreover, the proposed methods provide a framework of decentralized parameter allocation, which gives the extendability of this work.

LoRaWAN is one of the network technologies that provide a long-range wireless network at low energy consumption. However, the pure Aloha MAC protocol and the duty-cycle limitation at both end devices and gateway make LoRaWAN very sensitive to malicious behaviors in the MAC layer. Moreover, this kind of sensitivity makes the false-positives problem challenging for malicious behavior detection with simple threshold methods. This study investigates two malicious behaviors - greedy and attack on the MAC layer. Furthermore, by combining the threshold method with a Local Outlier Factor (LOF) model in machine learning, LoRaLOFT is proposed. It is a centralized malicious node detection method. Analytical results show that the proposed method gives high detection accuracy while significantly reducing the false-positive rate in both behaviors.

Smart Car Parks (SCPs) based on Wireless Sensor Networks (WSNs) are one of the most interesting Internet of Things applications. This paper addresses the deployment optimization problem of two-tiered WSNs dedicated to fire monitoring in SCPs. Networks deployed inside the SCP consist of three types of nodes: Sensor Nodes (SNs) which cover the spots within the parking area, Relay Nodes (RNs) which forward alert messages generated by SNs, and the Sink node which is connected to the outside world (e.g, firefighters), through a high bandwidth connection. We propose an algorithm based on chaos theory and Whale Optimization Algorithm (WOA), which minimizes simultaneously the deployed number of SNs, RNs, and network diameter while ensuring coverage and connectivity. To evaluate the effectiveness of our proposal, we have conducted extensive tests. The results show that the Chaos WOA (CWOA) outperforms the original WOA in terms of solution quality and computation time and by comparison with an exact method, CWOA provides results very close to the optimal in terms of fitness value and is efficient in terms of computational time when the problem becomes more complex.

As one of the technologies in the wide-area network category, LoRaWAN provides a wireless network with a large capacity of end devices (ED) in long-range. With a pure Aloha protocol implemented into its MAC layer, LoRaWAN can reduce its power consumption. Besides, some orthogonal transmission parameters give LoRaWAN capability to avoid collision and packet loss. Thus, allocating transmission parameters to increase the network performance becomes a challenging issue for LoRaWAN. Some dynamic Spreading Factor (SF) allocation strategies are studied in this paper. A distributed Markov Decision Process (MDP) model is constructed for the uplink transmission of the class-A device in LoRaWAN. The model is also solved and implemented to the algorithms for the initial strategy prediction. Analytical results show that the MDP model increases the performance of the studied algorithms on the transmission of the packet.

The last decade has witnessed an ever-growing user demand for a better QoS (Quality Of Service) and the fast growth of connected devices still put high pressure on the legacy network infrastructures. To improve network performances, better manage the resources and have a greater control over traffic transmission, intelligent routing procedures are increasingly demanded. Modern applications in the dynamic context of new emerging networks have their own routing requirements, in terms of set of metrics to consider, their importance and thresholds to respect. The objective of this work is to design an approach based on MCDM (Multi-Criteria Decision Making) to decide complex routing problems when assuming threshold constraints on metrics. We give the mathematical framework to capture such requirements and to decide the routing. A case study is presented to advocate the benefit of using our approach.

ABSTRACT In the inevitably hi‐tech universe of cybercrimes, one of the major still prevailing methods is the usage of the malicious URLs and creating a Phishing link to obtain user credentials from the people. This method is highly subtle and has more effect on people's lives as well as corporate loss. To identify the malicious URLs, the security community has listed blacklists and benign links online. Still, as the technology is being developed day by day, the attackers try to create new phishing URLs using new social engineering methods that could be easily forged into the user's account. To improve the generality of malicious URL detectors, machine‐learning techniques have been explored with increasing attention in recent years. This article addresses the detection of malicious URLs combining the intelligence of both the heuristic‐based method and the machine learning process. It has been found that there are many possibilities for detecting zero‐day attacks and spear‐phishing attacks when incorporating both lexical features and machine learning methods. Out of the six‐batch learning process analyzed, we implement a decision tree algorithm in our framework with 99.47% accuracy during evaluation. The true positive values gained in our proposed hybrid framework is 99.2% and indicate <1% of the false‐positive values. The implementation shows a precision level higher than the previous model developed and by other antiphishing techniques. A high detection rate on zero‐day and spear‐phishing attacks and overall results reveal that our system outclasses the current approach to detecting phishing scams.

As an original property of human beings, human emotion recognition has gained a lot of interests of many researchers. The recent emotion recognition scheme using wireless signal is considered as one of emerging techniques toward intelligent smart cities. It is highly reasonable to form virtual emotion barrier that can detect human emotion when people move from one side to another side through at least one device in the barrier using wireless signal. Also, it is critical that the emotion recognition delay by virtual emotion barrier with possible two-way detection must be minimized to provide emotion-based services to citizen in timely manner. In this article, we introduce a virtual emotion detection model with two-way enabled delay bound, which pursues to provide timely emotion-based IoT services in advanced smart cities. Also, we formally define a problem whose objective is to generate two-way enabled virtual emotion barriers such that the virtual emotion detection maximum delay of those barriers should be minimized. Then, we propose a novel Two-Way-Enabled-Border-Slab scheme and evaluate its performance through extensive simulations with various settings and scenarios. Furthermore, relevant to the proposed system, we discuss possible research issues, challenges and future works.

LoRaWAN (LOng RAnge radio Wide Area Network) belongs to the LPWAN (Low Power Wide Area Network) category, it aims to provide a wide area, long range and low power consumption communication network solution. However, with the large number of connected devices to the base-station and a pure Aloha MAC protocol, the packet lost and collisions become an important issue in the network related to the transmission parameters of the devices. For this issue, STEPS is proposed in this study. The goal of the proposed method is to establish a score table based evaluation and parameters surfing approach. STEPS provides an approach of evaluating and changing the parameters based on probability and score table when transmission failure appears. It can also update the table while transmitting. STEPS is compatible with pure Aloha, and doesn't need any change on the MAC protocol and is easy to be implemented. In this study, the spreading factor is chosen as the parameter to establish the table, that will be evaluated and to be surfed. Simulation results show that STEPS provides a remarkable improvement on bi-directional transmission of the packet and a capability of decreasing the packet lost and collisions even with higher data rate than classical LoRaWAN scenario.

Energy consumption reduction has become a key research area in Wireless Sensor Networks (WSNs). Several studies have been done in order to reduce energy consumption in WSN. However, only few of them have studied Quality of Service (QoS) criteria such as throughput and latency. Therefore, this study proposes a new hybrid protocol called MDC-LEACH-K, which is a combination between Low Energy Adaptive Clustering Hierarchy-K-Means LEACH-K (approach) and MDC, to improve the LEACH protocol. Specifically, the purpose of the proposed protocol is to extend the network life time and improve its quality of service criteria. Specifically, this protocol uses K-Means clustering algorithm to reduce energy consumption in Cluster Head (CH) election phase and to improve the election of CH. In addition, a mobile data collector (MDC) is used as an intermediate between the cluster head and the base station (BS) to further enhance the QoS criteria of WSN, to minimize time delays during data collection and to improve the transmission phase of LEACH protocol. The obtained simulation results demonstrate that MDC-LEACH-K had a considerable impact on energy consumption and QoS metrics. Particularly, this protocol achieves a significant energy gains by 296% of residual energy compared to Low Energy Adaptive Clustering Hierarchy protocol (LEACH), 237% to Threshold Sensitive Energy Efficient sensor Network protocol (TEEN), and 257% to Low Energy Adaptive Clustering Hierarchy-KMeans protocol (LEACH-K) and more than 100% compared to LEACH, TEEN, LEACH-K and MDC maximum residual energy LEACH protocols in latency time.

Wireless sensor networks (WSNs) are gaining an increasing attention due to their omnipresent nature and their wide deployment in the Internet of Things and other emerging fields. Despite this importance, little researchers focused on enhancing the Quality of Service (QoS) criteria of WSNs, particularly in hierarchical routing protocol. Therefore, this study proposed a new protocol to enhance the QoS of hierarchical routing protocols. In particular, LEACH-G-K is based on LEACH protocol. LEACH-G-K divided the area into equal size clusters using the grid function. Then, for each cluster, the K-means algorithms is applied to gather their nodes near to the centroid, where the cluster head is located. The obtained simulation results showed that LEACH-G-K can enhance the energy consumption and QoS criteria compared to Low Energy Adaptive Clustering Hierarchy protocol (LEACH), Threshold Sensitive Energy Efficient sensor Network protocol (TEEN), Low Energy Adaptive Clustering Hierarchy-KMeans protocol (LEACH-K) and MDC maximum residual energy LEACH protocols.

Mobility simulation models are important tools to the development of Intelligent Transportation Systems (ITS). These models allow to emulate the real-world characteristics of vehicular mobility operations in order to evaluate the capacity of ITS related protocols and services to deal with the highly dynamic mobility of vehicles. In this work, we provide a novel queuing theory based simulation model for vehicular mobility that functions in the Simulink/Matlab environment, and uses SimEvents toolbox. The proposed tool offers a graphic library composed of different modules each representing a mobility aspect. It is also suitable to simulate both urban and freeway scenarios under different traffic conditions. The model generates synthetic measures relevant to the assessment of road network performance such as average travel time, average delays and average queue lengths. A set of experiments are conducted to verify the ability of the model to reproduce the realistic behavior of vehicular traffic.

As one of the LPWAN categories, LoRaWAN attracts great attention on IoT and M2M communication. It offers a comprehensive area communication network solution with a low data rate and low power consumption. Many research works on medium scheduling or resource allocation have been proposed to improve network performance. However, with many devices in the network, it is sometimes too difficult to deploy a test-bed to evaluate the network performance in the industry. However, different studies often use different simulators. Thus, it is also challenging to study the impact of different algorithms on the network by simulation. Thus, an extendable simulator becomes necessary for both industrial networks deploying and academic study. In this paper, we developed a lightweight, extendable simulator exclusive to LoRaWAN named MULANE. We also offered a GUI is to simplify the simulation process. Moreover, the simulator is agent-oriented, making the research works implementation easier by creating new agents,

Vehicular Adhoc Network (VANET) is an innovative technology designed to tackle the road safety challenges by providing a communication infrastructure to vehicular environments. Safety-related applications are delay-intolerant and demand low-latency and reliable transmissions of critical data. TDMA mechanism has been proven effective for this type of applications. However, the particular features of the vehicular environment bring challenges to the applicability of TDMA in VANET. The highly dynamic nature of the network increases the likelihood of concurrent access to radio resources. Several studies addressed the access collision issue in TDMA, but they demonstrate weaknesses regarding channel utilization and negotiation overhead. In this paper, we present a traffic-aware TDMA-based (TA- TDMA) protocol which improves the VeMAC protocol to meet the real-time requirements. The proposed solution relies on traffic prediction to assign appropriate resources to each area of the network. To evaluate its validity, TA- TDMA is compared with VeMAC through simulation.

In this paper, a blockchain based scheme is proposed to provide registration, mutual authentication and data sharing in wireless sensor network. The proposed model consists of three types of nodes: coordinators, cluster heads and sensor nodes. A consortium blockchain is deployed on coordinator nodes. The smart contracts execute on coordinators to record the identities of legitimate nodes. Moreover, they authenticate nodes and facilitate in data sharing. When a sensor node communicate and accesses data of any other sensor node, both nodes mutually authenticate each other. The smart contract of data sharing is used to provide a secure communication and data exchange between sensor nodes. Moreover, the data of all the nodes is stored on the decentralized storage called interplanetary file system. The simulation results show the response time of IPFS and message size during authentication and registration.

Since a long time, the integrity of physical borders is seen as a challenging concern. Indeed, governments have to facilitate travelling and trade so that economies continue to grow while preventing the entry of dangerous entities. To this aim, several conventional techniques were enforced to secure borders in the recent past. However, due to the immensity of the area to be monitored, such solutions require an intensive human involvement and high maintenance costs. This advocated to use new technologies, such as Wireless Sensor Networks (WSN), to reduce the costs and improve the efficiency of the border surveillance system. Although using and combining these technologies has been already addressed in different existing solutions, it still some key points to be considered like energy efficiency, load balancing, and redundancy elimination. In this paper, we first propose a multilayer hybrid architecture based on cameras, scalar sensors, radars, and UAVs to design a border surveillance system. Then, a detailed deployment strategy is discussed. Finally, an activation scheduling strategy based on load balancing and energy saving is addressed. The simulation results show that our solution could not only detect the intrusion in border areas, but also outperforms the other solutions by managing efficiently the network and extending its lifetime.

Intelligent transport systems provide great possibilities to mitigate traffic congestion and intensify driving efficiency. The design of these systems requires a clear understanding of traffic dynamics. In this respect, this study focuses on describing and analysing traffic conditions at junctions in urban environments from a macroscopic level of description. As a first step, our method attempts to interpret the traffic scenario at intersections as a queuing system. Then, a Continuous Time Markov Chain to predict the future traffic condition at intersections is developed, and afterwards the pertaining steady-state probabilities are obtained. Given the equilibrium vector, significant performance measures are inferred for monitoring and planning purposes.

Nowadays, securing borders is becoming a real concern for all the countries over the world. Conventional methods which were widely used are quickly abandoned due to the intensive human involvement and high maintenance costs. Instead, new technologies, such as Wireless Sensor Networks (WSN), camera sensors and Unmanned Aerial Vehicles (UAVs) are deployed to reduce the costs and improve the efficiency of the borders surveillance system. However, there still remain some serious flaws, such as late intrusion detections due to the sensing range limitation of the sensors. To address this issue, we propose in this study a new hybrid multilayer architecture for border surveillance based on the combination of radars with mobile camera sensors that are embedded in UAVs. To overcome the short flight duration of UAVs (due to the batteries limitation), we propose the use of a Wireless Power Transfer system WPT based on rectennas to supply UAVs batteries with power during their flight. To manage the access of UAVs to the WPT system, we implement an active UAVs scheduling strategy based on an improved Weighted Round-Robin (WRR) algorithm. To evaluate our scheduling strategy, simulation results are presented and discussed.

Connected healthcare is the process of integrating healthcare smart applications into smart devices. These systems can enable better patient-hospital experience, efficient time usage, reduced errors, safety and security, and ultimately improved treatments. These smart devices which form an IoT network are extremely dynamic because of the user movement. In an environment where there is a constant change in the network topology and its traffic profile, it is a challenging task to provide reliable network connectivity and to maintain the IoT network. Therefore, ensuring healthcare traffic is resilient towards change in the traffic profile is of paramount importance. This paper leverages graph theory concepts to understand the behaviour of the healthcare IoT network. The paper highlights the importance of the PN (PN) and traffic splitting (stratification). A PN is a node in the network which has enough computing resources to share with other network devices. By optimizing the selection of PN, the drastic improvement in the network performance could be achieved. Moreover, we show that splitting the traffic along with optimized PN selection minimizes the chances of healthcare traffic drop during the period of high network usage.

Network slicing (NS) will have an essential role to enhance the isolation and the flexibility of the future generation of cellular networks (5G) with heterogeneous capabilities, notably in ultra-dense (UD) urban zones. Thus, it may be the principal component necessary to respond to 5G UD heterogeneous networks (UD-HetNets) technical requirements. The aim of this paper is to propose a new NS architecture to resolve user equipment (UE)-association problem in 5G UD-HetNets. Accordingly, we formulated the problem as a one-to-many matching game based on matching theory, while exploiting the isolation character of slicing to eliminate interferences between pico-cells and those among macro-cell and pico-cells. Next, we proposed the UE-slice association algorithm (U-S.AA) to find the stable matching among user equipments (UEs) and different network slices. Numerical simulation results validate our theoretical model, and prove the efficient of the proposed user-slice association solution to enhance the global network performance, respecting the UEs quality of service (QoS), as well as improving the energy efficiency (EE) of UEs.

Unmanned aerial vehicles (UAVs) are a promising technology employed as moving aggregators and wireless power transmitters for IoT networks. In this paper, we consider an UAV-IoT wireless energy and data transmission system and the decision-making problem is investigated. We aim at optimizing the nodes' utilities by defining a good packet delivery and energy transfer policy according to the system state. We formulate the problem as a Markov Decision Process (MDP) to tackle the successive decision issues. As the MDP formalism achieves its limits when the neighbors' interactions are considered, we formulate the problem as a Graph-based MDP (GMDP). We then propose a Mean-Field Approximation (MFA) algorithm to find a solution. The simulation results show that our framework achieves a good analysis of the system behavior.

Human emotion recognition has attracted much interest of researchers since it can be utilized for various applications and communication software services. For emotion recognition, there are several approaches including facial expression, human motion. In particular, the emotion derivation through wireless signal and its reflection has been developed recently. Also, a concept of virtual emotion barrier has been introduced, which the emotion can be detected by the built virtual emotion barrier. Because human emotion can be changed frequently, the emotion detection delay through virtual emotion barrier should be minimized for possible accurate emotion recognition. In this paper, we introduce delay bounded virtual emotion barriers in IoT-enabled smart cities, which deliberate on the minimum virtual emotion detection latency among the constructed virtual emotion barriers for next generation software services. Then, we formally define a problem whose goal is to create delay-bounded virtual emotion barriers in IoT-enabled area such that the virtual emotion detection maximum delay among virtual emotion barriers is minimized. To solve the problem, we devise a novel scheme which admits virtual emotion recognition with minimum delay. Furthermore, the performance of the proposed approach is evaluated through extensive experiments.

Securing physical borders is a critical task and a real concern for all the countries over the world. Conventional techniques which have been largely investigated to secure borders over the past, are progressively abandoned due to the intensive human involvement and high maintenance costs. Recently, new technologies, such as Wireless Sensor Networks (WSN), have been implemented to reduce the costs and improve the efficiency of the border surveillance system. One of the critical issue in WSN it to define an efficient activation strategy of the different sensors to reduce the resource consumption and enhance the lifetime of the network. We propose in this paper to study the effectiveness of adapting the activation period of scalar sensors and cameras on the lifetime of the network. Simulation results show that this period should be reduced in crisis time to enhance the fault tolerance of the network while it should be augmented in peacetime to extend the network lifetime.

Unmanned aerial vehicles (UAVs) are a promising technology to provide an energy-efficient and cost-effective solution for data collection from the ground Internet of Things (IoT) devices. In this paper, the optimal associations that provide reliable connections between UAVs and IoT devices are investigated. We aim at maximizing the IoT devices' benefits, by assigning them to most suitable UAVs. We formulate the problem as a many-to-one matching game where UAVs and IoT devices are the players. In this game, the players rank one another based on individual utility functions that capture their needs. Each IoT device aims to minimize its transmitting energy while meeting its SNR requirements and each UAV aims to maximize the number of served IoT devices while respecting its energy constraints. Simulation results show that the proposed approach provides a low average total transmit power, ensures fast data transmission and optimal utilization of the UAVs' bandwidth.

In this paper, a seamless virtual emotion system is introduced toward appropriate emotion-based services in advanced IoT-enabled smart cities. The proposed system is supported by virtual emotion barrier with replaceable detection and hole-free property, which recognizes human emotion using wireless signal. Also, we formally define a problem with ILP formulation whose goal is to maximize the lowest detection accuracy with weak hole in replaceable barrier in order to construct seamless replaceable hole-free virtual emotion barrier ultimately. Then, a novel scheme is proposed to solve the problem. Moreover, we perform the proposed approach through extensive simulations with various scenarios and its performance is evaluated with detailed discussion.

Wireless backhaul of outdoor small cells is a cost-effective solution in a dense heterogeneous network as it reduces the need to provide a wired connection for each small cell access point to the core network. On the other hand, non-orthogonal multiple access (NOMA) has emerged as a promising technology to improve the spectral efficiency of a network. This paper investigates the impact of applying NOMA at the backhaul of small cells to enhance the spectral efficiency of the system. However, this requires a careful pairing of desired small cells to increase the system performance of NOMA. In this regard, a joint pairing and resource (bandwidth and power) allocation scheme for the backhaul of small cells is studied based on the load of the small cells. Furthermore, our performance evaluation shows that the proposed scheme outperforms the existing user pairing approaches in terms of achieving high spectral efficiency.

Mobile cellular users traveling in city buses are experiencing poor quality of signals due to the interference and the large number of mobile devices. To enhance the Quality-of-Service (QoS), deployment of small cell networks in city buses is a promising solution. The deployment of small cells in vehicular environment makes the resource allocation more challenging because of the dynamic interference relationships experienced by them. Therefore, resource allocation in vehicular environment within moving small cells (MSCs) needs to be handled carefully. In this study, we investigate the problem of resource allocation in city bus transit system with multiple routes. Then, we propose a Percentage Threshold Interference Graph (PTIG) based allocation of resources to MSCs in a network. City buses of multiple routes travel with variable speed and may share some of the same road segments which make it difficult to extract the exact interference patterns between them. Therefore, Long Short Term Memory (LSTM) neural networks are used to predict the city buses locations. The predicted locations of city buses are then used to generate PTIG by finding the dynamic interference relationship between MSCs. Graph coloring algorithm is used to allocate the resources to PTIG. Numerical results are presented to show the comparison of resource allocation using PTIG and Time Interval based Interference Graph (TIIG) in terms of resource block utilization and time complexity.

Summary We consider a mobile delay‐tolerant networks (MDTNs) with energy‐harvesting capabilities. In order to determine energy management policies that will improve network capacity and packet delivery ratio and maximize the system throughput, we consider a source node that seeks to send packets to a destination node. The optimal policy for the source varies according to its system state, which allows it to guarantee a maximum delivery probability rate. Our problem is modeled by decision theory; as a start, we are interested in the MDP to model and solve such sequential decision problems. Our goal is to optimize for each node, a utility depending on a random environment and decisions made by the node. As the MDP formalism reaches its limits when it is necessary to take into account the interactions between different several nodes, we will start using the graph‐based MDP where the state and action spaces are factorizable by variables. The transition functions and rewards are then decomposed into local functions and the dependency relations between the nodes are represented by a graph. To calculate the optimal policy, we propose Mean Field Approximation (MFA) and Approximate linear‐programming (ALP) algorithms for solving GMDP problem.

Underwater Sensor Network (UWSN) suffers from the limited batteries life of sensor nodes. Thus, some nodes will disappear from the network topology during the communication process which leads to isolated nodes and important buffered packets will be discarded. Traditional greedy forwarding protocol used in UWS N s are based on the selection of the nearest next-hop forwarder from the destination, that's the nearest one from the sea surface relaying the source and destination. By this, some nodes are selected by multiple source nodes, so their energy risk to be drained. In order to overcome this problem, we enhance this protocol by distributing the forwarding task between multiple next-hop forwarders. Also, this protocol is based on depth adjustment to solve the problem of isolated nodes. The source packet is splitted and each sub-packet is transmitted to a single upper neighbor node. Otherwise, multiple data channels are used to avoid collision between source nodes selecting the same next-hop node. Numerical results show significant improvement in greedy forwarding protocol performance.

With the explosive growth of mobile multimedia traffic, the problem of allocating computing and spectral resources for very low latency services become a challenge for next generation mobile networks. We exploit all the benefits of a completely virtualized environment, where mobile virtual network operators (MVNOs) and virtual service providers (VSPs) are connected in the Cloud through network as a service (NaaS) using distributed infrastructure as a service (IaaS). VSPs provide services according to Internet of things (IoT) devices requests including software as a service (SaaS) and emerging caching techniques Cache as a Service (CaaS) to satisfy the quality of service (QoS) requirements. Thus, we propose a many-to-many matching game between the sets of IoT devices and the set of virtual service providers (VSPs). To solve this game, we exploit the deferred acceptance algorithm that enables the players to self-organize into a stable matching and a reasonable number of algorithm iterations. To highlight the effectiveness of our approach for the on-demand services, we applied it on two typical services requiring ultra- reliability and low-latency communications (uRLLC): The intelligent transport and the video on-demand services. Simulation results has demonstrated that our proposed matching strategy coupled to CaaS caching capabilities on distributed F-RAN significantly outperforms the traditional strategies in terms of latency and network traffic load.

5G Network architecture based on the ultra-dense deployment of millimeter-micro wave (mmW-µW) HetNets is a promising solution to maximize revenue and business potential of mobile network operators (MNOs). However, in the near future, MNOs are urged to manage these network architectures that will serve a large number of mobile subscribes with distinctive user profiles (Gold, Silver, Bronze or Best effort), and individual quality of service (QoS) requirements. In this paper, we provide a new user association scheme that take into consideration the profile and QoS requirements of each mobile user. Our association problem is formulated as a one-to-many matching game inspired from matching theory. Then, we propose two distributed differed acceptance algorithms executed successively to achieve two stables matching. The first one consists of assigning each gold mobile users to the most suitable mmW-µW base stations(BSs). Next, based on the first stable matching results, the second one consists of assigning each best effort user to the most suitable mmW-µW BSs without degrading the QoS of gold users. Simulation results corroborate our solution, and show its effectiveness by enhancing the average sum rate performance, while respecting the profile and QoS requirements of mobile users compared to the conventional Max-SINR and Max-RSSI association schemes

Macro-small cells networks, which include a multiple small cells under the macro cell area, provide an attractive solution for meeting capacity requirements of the network and achieve higher user data rate transmission. The deployment of small cells also is an effective approach to reuse the spectrum that provide an increasing spatial reuse of bandwidth. In this study, we propose a game model to manage the macro user association in the heterogeneous network architecture composed of one single macro base station and a set of small-cells operating in the same spectrum. We construct an utility gain framework to allow macro base station to encourage macro users to play the same strategy (defined as a recommended small base station that offers a high throughput to the macro user with low interference, because the macro base station is considered as a controller of the current users under different small base stations) in order to help them to get an acceptable throughput. We obtain the best distribution of macro users equipment among small-cells and macro base station. The proposed game model is done in the dynamic and randomly environment. We use the Combined fully distributed payoff and strategy learning algorithm to prove in one side the existence of Nash equilibrium and to accelerate the convergence in the other side.

5G ultra-dense multi-Radio access technology (Multi-RAT) HetNets are considered recently, by industrials and mobile network operators, as a key solutions for boosting network capacity. Hence, supporting the exponentially increasing demand of data traffic. However, improving multiple conflicting metrics for users, with distinctive quality of service (QoS) and quality of experience (QoE) requirements, remains the main challenge in these network environments. This is due to the inappropriate adaptation of the current user association schemes. To overcome this challenge, we formulated the user association problem, in 5G ultra-dense multi-RAT HetNets, as a multi-objective optimization problem (MOOP), solved by the weighted sum method. Then, we proposed the multi-objective genetic algorithm (MOGA) to reach suitable associations, that respect the individual requirements of each user. Numerical results show the potency of the MOGA with decoupled access (MOGA-DA) compared to the MOGA with coupled access (MOGA-CA) and Max-SINR (Signal-to-Interference-plus-Noise Ratio) association schemes in terms of energy efficiency (EE), cost efficiency (CE) and QoS uplink/downlink throughput.

A barrier-coverage has attracted much interests of researchers because it can guarantee to detect any movement of mobile objects. Also, thanks to recent advancement of technology, it is possible to recognize human emotion by facial expression and human motion or activity. Then, the emotion recognition can be applied to various services and applications appropriately. Recently, it has been developed to sense emotion by wireless signal. One of issues for emotion recognition is to increase the recognition accuracy. In this paper, we introduce a new type of barrier, virtual emotion barrier, which is able to detect emotion by devices with wireless signal in Internet of Things (IoT) environment. Then, we formally define a problem whose objective is to construct virtual emotion barrier in the given area including IoT devices such that the detection accuracy of emotion by virtual emotion barrier is maximized. To solve the problem, we propose a greedy-emotion-accuracy approach. Moreover, we discuss future issues and possible research directions for virtual emotion barrier.

Wireless Sensor Networks (WSNs) are formed of a set of tiny autonomous entities interconnected by wireless communication links. These entities cooperate to collect and transmit measures taken from their environment. WSNs are characterized by a limitation of their battery, processing power and storage memory, which makes the consumption energy saving a real challenge. However, WSNs are deployed in open radio frequency and lack of physical security. Thus, these networks are vulnerable to several attacks: passive eavesdropping; active attacks; identity theft. In this paper, by using Stochastic Automata Networks (SAN), we propose to model our proposed method named Accordion method in order to detect and apprehend Denial of Service attacks (DoS).

We consider a mobile delay tolerant networks (MDTNs) with energy harvesting and wireless energy transfer capabilities. In order to determine energy management policies that will improve network capacity, packet delivery ratio and maximize the system throughput. We consider that a source node seeks to send packets to a destination node. The optimal policy for the source is varies according to its system state, which will guarantee a maximum delivery probability rate. Each mobile source node transmits wirelessly a portion of its energy as a reward to relay mode. Our problem is modeled by decision theory; as a start, we are interested in the MDP, which are used to model and solve such sequential decision problems. In this paper, for each node, we try to optimize a utility depending on a random environment and decisions made by a node. As the MDP formalism reaches its limits when it is necessary to take into account the interactions between the different several nodes, that's why we chose to use the Multi agents Markov Decision Processes (MMDP) which is a MDP with a large space of states and actions. The set of agents are then considered as a single agents whose goal are to compute an optimal attached policy for MDP. To make a realistic analysis of our model, we assume that the policy of the MMDP is applied in a decentralized way, which makes finding optimal control intractable; thus, we will develop several approximations and evaluate their effectiveness.

With the explosive growth of mobile multimedia traffic, content caching is seen as an effective solution to alleviate the heavy traffic burden on back-haul and front-haul and to improve the quality of real-time data services. The concept of ”Cache as a Service (CaaS)” is a framework for caching virtualization for mobile cloud-based networks. Consequently, contents can be distributed and stored based on their popularity, traffic diversity, and diverse user demands. In this paper, we mainly consider the problem of allocating computing resources for very low latency services, as well as high data rate services that require sufficient spectral resources. We plan to exploit all the benefits of a completely virtualized environment, where mobile virtual network operators (MVNOs) and virtual service providers (VSPs) are connected in the Cloud through network as a service (NaaS) using distributed infrastructure as a service (IaaS). VSPs provide service to (Internet of things) IoT devices including software as a service (SaaS). The IoT devices, as a service requester will take advantage of emerging caching techniques (CaaS) to accomplish the on-demand low-latency services that require a large amount of computing resources and a high bandwidth. In order to satisfy the quality of service (QoS) requirements, the radio access network RAN as a Service (RANaaS) is the pivot of this environment that will allocate dynamically networking, computing and storage resources according to the required services in terms of latency and throughput. Thus we propose a many-to-many matching game between the sets of IoT devices and the set of virtual service providers (VSPs). To solve this game, we exploit the deferred acceptance algorithm that enables the players to self-organize into a stable matching and a reasonable number of algorithm iterations. The goal of the proposed manyto-many game theory approach is to optimize the caching spaces that VSP exploit in the edge to store files or software required by IoT devices. Simulation results has demonstrated that our proposed matching strategy coupled to CaaS caching capabilities on distributed F-RAN significantly outperforms the traditional caching strategies in terms of the cache hit ratio, average latency and back-haul traffic load.

MANETs (Mobile Ad hoc NETworks) are characterized by a dynamic topology and generally deployed in a hostile environment with limited resources. Therefore, the design of fault tolerant applications in this environment is paramount as nodes are often subject to failures. We exploit in this paper a solution based on geographic area node repartition to provide a virtual centralization of the network to monitor the failure detection procedure. Hence, we define our protocol called, ARFAD (Area Repartition Failure Detection) that allows a fast detection of a failure while reducing significantly the traffic overhead. We report simulation results performed on NS2 platform that compare the performances of ARFAD with a recent protocol.

The technological advancement has been accompanied with many issues to the information: security, privacy, and integrity. Malware is one of the security issues that threaten computer system. Ransomware is a type of malicious software that threatens to publish the victim's data or perpetually block access to it unless a ransom is paid. This paper investigates the intrusion of WannaCry ransomware and the possible detection of the ransomware using static and dynamic analysis. From the analysis, the features of the malware were extracted and detection has been done using those features. The intrusion detection technique used here in this study is Yara-rule based detection which involves an attempt to define a set of rules which comprises of unique strings which is decoded from the wannacry file.

Device-to-Device (D2D) communication is a promising technology to enhance spectrum efficiency and improve system capacity. One of the major problems in spectral reuse is the important interference to the cellular network when they both share the same resources. This paper considers the channel assignment problem for D2D communication underlaying cellular networks. Our goal is to maximize the overall system throughput by applying an approach based on regret-matching learning while the constraints related to the quality of service of the users are respected. We formulate the problem as a non-cooperative game where players (D2D player) choose the channel that maximizes their utility function by learning their best strategy (based on the regret observed by playing an action). The advantage of regret matching is that it is distributed and involves limited information exchanges among players. The algorithm shows relatively fast convergence to the set of correlated equilibrium and near optimal performance after a small number of iterations.

Wireless sensors and multimedia communications are increasingly becoming a part of our everyday lives and societies.Subsequently, issues surrounding their safety and security are becoming ever more important.The situation is true, not only for overtly hostile environments such as for defense and public security, but also for covert commercial platforms handling private and sensitive information.Also, with the advent of new devices and circuits from the development of military systems, a host of new technologies have come to the fore, including sophisticated RF sensing, activating, signal processing, and communications.The prompt ability to protect against hostile actions to sense, access, process, command, and control covert information is of utmost importance and is vital for the success of this next generation of communication systems and networks.This special issue presents several research results in covert communication networks in hostile environments, including the identification of current challenges for each domain, the development of novel technologies and strategies, and discussion and exploration of future solutions.The first challenge of the cover communications and networks is how to confront the hostile noises or environments.Historically, for communication engineers, the white Gaussian is the least favorable noise [1], and conventional system designer considers the best design under the least favorable Gaussian or combination of the multiple or variational Gaussian, such as Rician, Nakagami, or others in [2].However, the hostile noises are far from the natural Gaussian shape and are rather close to typical signals such as single tone and sweep sinusoidal jamming.Further, the hostile noise is very intentional, having less information in theory in other words.Subsequently, we may fully utilize the known and

We consider a mobile delay tolerant networks (MDTNs) with energy harvesting capabilities. In order to determine energy management policies that will improve network capacity, packet delivery ratio and maximize the system throughput. we consider that a source node seeks to send packets to a destination node. The optimal policy for the source varies according to its system state, which allows it to guarantee a maximum delivery probability rate. Our problem is modeled by decision theory; as a start, We are interested in the MDP, which are used to model and solve such sequential decision problems. Our goal is to optimize, for each node, a utility depending on a random environment and decisions made by the node. As the MDP formalism reaches its limits when it is necessary to take into account the interactions between the different several nodes, we will start using the Graph-based MDP where the state and action spaces are factorizable by variables. The transition functions and rewards are then decomposed into local functions and the dependency relations between the nodes are represented by a graph. To calculate the optimal policy, we propose Mean Field Approximation (MFA) and Approximate linear-programming (ALP) algorithms for solving GMDP problem.

A recent proliferation of UAVs accompanies several critical issues to be considered for efficient, secure use of UAVs. One of those issues should be a privacy of people. Also, when the UAVs fly to perform specific objectives, minimizing movements of UAVs is a big issue to provide a minimum mission completion time and a maximum network lifetime. One intuitive solution is that UAVs may pass through private area of citizens whereas people do not want any penetration into own area without a permission. Then, we may take into account a compromise between those situations by giving a differential permission for each UAV to access citizens' areas depending on specific benefits by use of UAVs or emergent situation for public safety. In this paper, we introduce a framework for privacy-preserving movements of UAVs with differential UAVs' permissions given by citizens. Then, we formally define a problem whose objective is to minimize total movements of UAVs with preserving privacy of people. To solve the problem, we create a new graph type called as UDiPP graph and propose a novel priority-based approach. Furthermore, we discuss future issues and directions for differential privacy-preserving movements by UAVs.

Congestion in Wireless Multimedia Sensor Networks (WMSN) may cause packet loss, buffer overflow and increases queueing delay, which has a significant negative impact on the network performance and reliability. This problem imposes more resource constraints that involve energy consumption and buffer size to meet additional requirements such as desired buffer size and limited amount of packet loss. One of the fundamental issues of congestion problem in such networks is the queue management. In fact, handling congestion without considering flexible buffer management and queueing methods, stay insignificant against dropping rate and packet loss. Consequently, a novel congestion control approach is needed to overcome these problems. In this paper, a new queue management mechanism called: Priority Queue Management based Explicit Congestion Control (PQMECC) is proposed and modeled using Stochastic Automata Networks, which are appropriate for modeling and analyzing complex systems with interacting components and complex synchronization. The congestion control technique used in PQMECC is based on priority, load repartition mechanism and explicit congestion notification which is generated only if the congestion reaches the threshold value.

In this paper, we propose a new version of the LBRW (Learning based Random Walk), LBRW-Co, for predicting users co-occurrence based on mobility homophily and social links. More precisely, we analyze and mine jointly spatio-temporal and social features with the aim to predict and rank users co-occurrences. Experiments are performed on the Foursquare LBSN with accurate and refined measurements. Experimental results demonstrate that our LBRW-Co model have substantial advantages over baseline approaches in predicting and ranking co-occurrence interactions.

In this paper, we propose a game-theoretic approach to find the community structure in complex networks based on a non-cooperative game. This approach optimizes a node-based modularity for non-overlapping communities. Experiments show that our approach is effective to discover non-overlapping communities and obtain high values of modularity and Normalized Mutual Information (NMI) for real-world and synthetic networks in a reasonable time.

With the diversity of services and the need of different traffic classes in wireless networks, WIMAX technology (Worldwide Interoperability for Microwave Access), has been developed as a broadband wireless access technology based on IEEE standard 802.16. Indeed, this technology is able to mix real time and non real time services with the definition of service classes. To improve the admission rate of the different classes when implementing the admission control component, we propose in this paper a traffic scheduling based on WRR policy and a new mechanism to handle the rejected requests. Finally, we provide the Markov Chain based modelling of our solution and compute thereof primary performance evaluation results.

The wireless shared medium used by Wireless Sensor Networks applications causes a problem related to interference, specially with dense deployment that characterizes the WSNs. This requires the use of congestion control scheme to avoid interferences and buffer overflow that degrade the application reliability. REFIACC (Reliable, Efficient, fair and Interference aware Congestion control) schedule scheme is a cross layer congestion control protocol that avoids the aforementioned problems while maximizing throughput and fairness. In our previously studies, we have validated REFIACC using extensive simulations. In this study, REFIACC is modeled using Stochastic Automata Networks (SAN). In fact, SAN presents a good tool to avoid state-space explosion of Markov chains.

Summary Recently, barrier‐coverage in wireless sensor networks is a critical issue because it can be used for various applications (e.g., intrusion detection and border protection). Many existing works for barrier‐coverage assume that an intruder penetrates through two opposite sides such as from top to bottom or from bottom to top and focus on constructing barriers to detect those penetrations. However, in many practical scenarios, it should be desirable to detect an intruder that enters the area of interest through any of its sides and passes through any other of its sides. In this paper, we introduce a new barrier‐coverage problem whose goal is maximizing the network lifetime such that any penetration variation of the attacker is guaranteed to be detected. In order to solve the problem, we create a new type of sensor barriers, which is referred asreinforced barriers, that can sense any movement variation of the intruder. Also, we propose four different approaches to construct reinforced barriers from a given layout of sensors and we compare their relative performances for maximum number of reinforced barriers through extensive simulations by various scenarios. Copyright © 2016 John Wiley & Sons, Ltd.

Summary The use of wireless sensor networks (WSNs) has increased rapidly over the last years. Due to their low resources, sensors come along with new issues regarding network security and energy consumption. Focusing on the network availability, previous studies proposed to protect clustered network against denial of service attacks with the use of traffic monitoring agents on some nodes. Those control nodes have to analyze the traffic inside a cluster and to send warnings to the cluster head whenever an abnormal behavior (e.g., high packets throughput or non‐retransmission of packets) is detected. But if the control nodes (cNodes) die out of exhaustion, they leave the network unprotected. To better fight against attacks, we try to enhance this solution by renewing periodically the election process. Furthermore, we propose three energy‐aware and secure methods to designate thecNodesin a hierarchically clustered WSN. The first one is a simple self‐election process where nodes randomly designate themselves. It leads to a better load balancing than a static method (i.e., with no renewal), but we argue that we can obtain better results by considering the remaining energy of the nodes atcNodesselection time. Hence, the second algorithm is purely based on the residual energy of the sensors. We discuss limitations of this deterministic process concerning security and cluster coverage and suggest workarounds. These improvements lead us to the third mechanism. It is based on residual energy too, but it includes a democratic election process in which nodes in the cluster vote to optimize thecNoderole attribution. Results obtained from simulation experiments with thens‐2tool are provided to analyze the energy repartition in the network and to compare the three selection algorithms. All experimental outcomes show improvements of the load balancing in the network, while maintaining good detection coverage, in regard to static selection. Furthermore, the analysis of the respective performances of the three mechanisms is used as a basis to establish recommendations regarding the use cases of those methods. Copyright © 2017 John Wiley & Sons, Ltd.

Vehicular Ad hoc Networks (VANETs), whose main objective is to provide road safety and enhance the driving conditions, are exposed to several kinds of attacks such as Denial of Service (DoS) attacks which affect the availability of the underlying services for legitimate users. We focus especially on the greedy behavior which has been extensively addressed in the literature for Wireless LAN (WLAN) and for Mobile Ad hoc Networks (MANETs). However, this attack has been much less studied in the context of VANETs. This is mainly because the detection of a greedy behavior is much more difficult for high mobility networks such as VANETs. In this paper, we propose a new detection approach called GDVAN (Greedy Detection for VANETs) for greedy behavior attacks in VANETs. The process to conduct the proposed method mainly consists of two phases, which are namely the suspicion phase and the decision phase. The suspicion phase is based on the linear regression mathematical concept while decision phase is based on a fuzzy logic decision scheme. The proposed algorithm not only detects the existence of a greedy behavior but also establishes a list of the potentially compromised nodes using three newly defined metrics. In addition to being passive, one of the major advantages of our technique is that it can be executed by any node of the network and does not require any modification of the IEEE 802.11p standard. Moreover, the practical effectiveness and efficiency of the proposed approach are corroborated through simulations and experiments.

Recent trends in mobile cellular networks turn towards deployment of Small Cell Networks (SCNs), where the cell size gets smaller and thus the number of subscribers served in a cell will be relatively smaller and should be considered finite. However, almost works on cellular mobile networks consider an infinite population cell, resulting commonly in infinite queueing models, for which no analytical solution is available for performance measures and only numerical approximations can be obtained. In this paper, a Call Admission Control (CAC) in a finite population micro-cell operating in a SCN, with retrials of blocked new calls, impatience of subscribers and multiple guard channels dedicated to handoff calls, is proposed. For the numerical computation of the steady-state probabilities of the corresponding continuous time Markov chain (CTMC), an efficient algorithm giving automatically the infinitesimal generator is developed, and various performance measures are established in network parameters and stationary probabilities. The guard channels number and retrials effect on the network performance in terms of blocking probability (for new calls and retrials) and dropping probability (of handoffs) is also carried out via experimental results.

Recently, Unmanned Aerial Vehicle (UAV) networks attracts a lot of interest as one of promising research areas since it can be used for a large portfolio of relevant applications. Among several issues in UAV networks, a collision avoidance among multiple UAVs should be addressed due to its significance. Furthermore, a barrier-coverage is considered as an important coverage concept because it is also appropriate for various applications such as intrusion detection and border surveillance. In this paper, we introduce a barrier-coverage system in UAV networks to construct collision-free UAV reinforced barrier. Then, we formally define a problem whose objective is to minimize total moving distance of UAVs such that collision-free is guaranteed among multiple UAVs when they move from initial locations to positions of constructing a reinforced barrier. To solve the problem, we introduce a novel strategy based on dividing a region into zones and describe our proposed approach. Moreover, we discuss future issues for barrier-coverage of UAV networks.

In this paper, we present the Enhanced Learning Based Random Walk (ELBRW) recommender system for Places of Interest (POI), which leverages contextual information for providing more relevant POI recommendations. The ELBRW considers a model of contextual factors namely POI crowdedness based on a discrete-time Markov chain and combines user interests and "mobility homophily" for POI recommendation in Location- Based Social Networks (LBSNs). By comparing it to the Learning Based Random Walk (LBRW), a context- free recommender system, the performed experiments using LBSNs data provide promising results in terms of POI recommendation quality.

In this paper, we propose a green solution for cellular users located in hyper dense co-channel deployments of LTE small cell networks (SCNs), randomly distributed within LTE macro cell networks (MCNs). Our solution is based on a distributed sharing time access algorithm executed by small base stations (SBSs), and multi-homing capabilities of macro cellular users to improve the energy efficiency of cellular users and to satisfy their QoS throughput requirements. The theoretical analysis is validated by simulations. Our results demonstrate the improved energy efficiency of cellular users compared to the other access control mechanisms.

Wireless Sensor Network (WSN) has recently emerged as a new widely used technology. However, the deployment of such networks has reported high rates of failures. Due to resource constraints of sensor nodes, the design of efficient failure detection techniques has become a very challenging issue. Already proposed WSN fault detection protocols have reported either a high number of false suspicions, or slow detection times, even an important message overhead which impact negatively the resource consumption of the nodes. In this paper, we propose EAFD (efficient and accurate failure detector), a novel protocol for failure detection for clustered WSNs. This protocol exploits two levels of suspicions to decide the failure of a node, as well as computation messages to disseminate the heartbeat of nodes during the detection process. Thereby, EAFD achieves a better compromise in terms of accuracy and completeness, as well as message overhead. Primary simulation results, found that our protocol outperforms the protocol AFD.

Cognitive radio is emerging as a promising technique to improve the utilization of the radio frequency spectrum in wireless networks. In this paper, we propose a hybrid CR (cognitive radio) system where underlay and overlay CR approaches are combined under SINR (Signal to Interference plus Noise Ratio) constraints. This new access type allows to optimize the spectrum sensing time with throughput improvement. The goal of this paper is to provide a new access mode in order to enhance the cognitive system performance while reducing the power spent for detecting the presence of the primary user and the spectrum holes. We consider the problem of spectrum sharing among primary (or “licensed”) users (PUs) and secondary (or “unlicensed”) users (SUs). In this scheme, the spectrum allocation problem is modeled as a non cooperative game, with each CR user acting as a player. Nash equilibrium is considered as the solution of this game.

A barrier-coverage in wireless sensor networks (WSN), which is able to detect a mobile object from one side to another opposite side, is a critical problem for lots of applications. Because it is highly appropriate to consider a barrier-coverage in event-driven environment, Kim et al. recently introduced k-event-driven partial barriers (k-EP barriers) with static sensor nodes, which at least k sensors can detect or monitor every movement of mobile objects on paths among multiple hubs in event-driven environment. But, in case of failures of sensors, k-EP barriers should be recovered from those failures. In this paper, we introduce resilient event-driven partial barriers with mobile sensors, which can maintain k-EP barriers continuously as well as can recover from a failed status when there exist failed sensors on initially constructed k-EP barriers due to energy depletion of those sensors. Also, we formally define a problem whose objective is to minimize total moving distance of mobile sensors such that k-EP are maintained continuously by considering movements of mobile sensors. To solve the problem, we propose a novel approach to minimize total movement distance of mobile sensors to form k-EP barriers continuously. Then, we address future issues and directions for resilient event-driven partial barriers.

Recent advances in wireless network technologies, like the ability to operate in a high-speed mobility environment, have opened up to a number of domains such as that of Intelligent Transport Systems (ITS) whose main component are so-called Vehicular Ad hoc Networks (VANETs). VANETs are associated with two kind of deployments: vehicular to Infrastructure (V2I), managing communications between vehicles and a fixed infrastructure, and Vehicular to Vehicular (V2V), for communications between vehicles. Since VANETs obey to the principles of mobile ad hoc networks, hence connections are established in a spontaneous and distributed manner, they suffer from lack of Quality of service guarantees as the access is not bounded. Modeling of VANETs is a complex task, as there are a number of factors that negatively affect the state-space dimension (i.e. the number of considered vehicles, the considered traffic, the mobility management). In this paper we introduce a formal model, in terms of a Markov chain, of the IEEE 802.11p MAC protocol, the basic access control mechanism employed in VANETs. Such model is the basis for computing relevant performance measures of the VANETs.

To guarantee fault tolerant system, checkpointing protocols are usually run to save the last consistent state of the system. This information will be recovered whenever a node failure occurs, thereby making it possible to resume the execution of the system. In the context of MANETs, checkpoints need to be saved in a safe and a stable storage to avoid data loss. Due the the specific constraints of such networks, the implementation of a stable storage (SS) is a hard task to achieve. So far, the most used techniques are based on mirroring or replication. However, although the latter achieve a safe an a reliable implementation of the SS, the deployment and the maintenance of the SS remain very costly. We explore in this paper a solution based on a distributed implementation of the SS by using RAID5 storage scheme. Mobile agent paradigm and geographic areas repartition of nodes are exploited to provide a virtual centralisation of the system. We associate this solution with a recent checkpointing protocol to provide an efficient fault tolerance tool for MANETs. Simulation results performed on NS2 show that our solution outperforms clearly replication.

Abstract The core of cognitive radio paradigm is to introduce cognitive devices able to opportunistically access the licensed radio bands. The coexistence of licensed and unlicensed users prescribes an effective spectrum hole‐detection and a non‐interfering sharing of those frequencies. Collaborative resource allocation and spectrum information exchange are required but often costly in terms of energy and delay. In this paper, each secondary user (SU) can achieve spectrum sensing and data transmission through a coalitional game‐based mechanism. SUs are called upon to report their sensing results to the elected coalition head, which properly decides on the channel state and the transmitter in each time slot according to a proposed algorithm. The goal of this paper is to provide a more holistic view on the spectrum and enhance the cognitive system performance through SUs behavior analysis. We formulate the problem as a coalitional game in partition form with non‐transferable utility, and we investigate on the impact of both coalition formation and the combining reports costs. We discuss the Nash Equilibrium solution for our coalitional game and propose a distributed strategic learning algorithm to illustrate a concrete case of coalition formation and the SUs competitive and cooperative behaviors inter‐coalitions and intra‐coalitions. We show through simulations that cognitive network performances, the energy consumption and transmission delay, improve evidently with the proposed scheme. Copyright © 2016 John Wiley & Sons, Ltd.

Failure detection in distributed systems under MANET environment is a hard task to achieve. Indeed, due to mobility and resource constraints, traditional protocols record a high number of false suspicions. We propose in this paper a new failure detection protocol for MANETs that achieves a better compromise in terms of accuracy and completeness, by introducing new mechanisms to correct false suspicions. Simulation results are reported to compare the performances of our protocol with other approaches.

The aim of this paper is to give a detailed modeling and performance analysis of Small Cell wireless Networks considering the limited number of mobiles served in each cell and different vacation schemes of the base stations channels, using the Generalized Stochastic Petri nets formalism. Hence, we show how this high level formalism allows a simple construction of detailed and compact models for such networks by considering single and multiple independent vacations of channels or all the base station in the case of synchronous vacations. In addition, we develop the formulas of the main stationary performance measures. Through numerical examples, we discuss the impact of channels number of the base station, vacation rate and vacation scheme on the network performances.

In heterogeneous network environments, users need to have mechanisms in place to decide which network is the most suitable at each moment in time for every application that the user requires. Always Best Connected is considered as a special concept to allow users to get connected to Internet using the access technology that best suits their needs or profile at any point in time. Clearly, this concept provides multiple access simultaneously for mobile users moving in heterogeneous access network environment. In this paper, we introduce a signaling game approach to achieve an always best connected service in vehicular networks. Under the considered scenario, we consider two smart vehicles named player 1 and player 2 moving in a road network area equipped with heterogeneous access networks. We assume that player 1 (super player) only has complete information on the road network, whilst player 2 has not any information. Player 1 plays first and sends a signal to player 2 which can be accurate or distorted. Based on the received signal and his belief about that signal, player 2 chooses its own action: it computes its suitable path which provides it an always best connected service.

In this era of big data, of quantified self and of smart cities, wireless sensor networks are meant to be used every day, for all sort of applications. Made of tiny sensors, they collect data and communicate through wireless technologies. Because they may take part in sensitive or military applications, security is an essential matter in such networks. Confidentiality and authenticity can be ensured by the use of dedicated mechanisms. Focusing on availability, we propose here a new practical approach to protect the network against denial of service attacks thanks to the use of traffic monitoring agents called cNodes. The approach uses a fair election process of cNodes in accordance with classical criteria related to residual energies and the presence of compromised nodes which may have greedy or jamming behaviors. Results obtained from simulations show that this method is effective both in terms of detection and of energy conservation.

Wireless Multimedia Sensors Networks are characterized by a high consumption of network resources such as energy and bandwidth. This consumption is caused by the large amount of data flowing across the network. One of the mechanisms used to reduce the consumption of resources is data fusion to eliminate redundant transmission while synthesizing the relevant information. However, as data fusion can operate only on specific nodes, called fusion agents, an important amount of data still remains sent from sensor nodes to the fusion agents. In this paper, we deal with the fusion of Multi-focus images. In such applications the totality of the images are sent from the cameras to the fusion agents before to be fused, which results in a huge consumption of the network resources. To tackle this issue, we propose a transmitting strategy that determines the useful information to send. This is achieved by computing different similarity coefficients at different levels. The values of the similarity thresholds are adaptable making it possible to cope with the context of the network and the running application. Primary simulation results show the effectiveness of the proposed mechanism in terms of network resources consumption and delay transmission.

Sensor networks are tiny independent devices which are characterized by limiting battery, processing power and storage memory, that makes saving consumption energy as real challenge power. Morever, there are many techniques used used to conserve energy in Wireless Sensor Networks (WSNs) the clustering technique is one of them. In terms of security, WSNs are more vulnerable to attacks than wired networks. However, radio frequencies used in WSNs are open, making the eavesdropping fairly easy. By considering energy consumption and in order to prevent from Denial of Service (DoS) attacks, present study introducing a preventing DoS attacks approach, which is based on using clustering techniques.

In this paper we present a formal modeling and analysis approach of the IEEE 802.11 CSMA/CA protocol in wireless local area networks (LANs) whose some greedy stations have selfish behaviors. Such stations do not strictly comply with rules of CSMA/CA protocol in order to increase their chances to access the channel at the expense of normal stations. We capture the behavior of wireless stations correctly implementing the DCF functioning mode of CSMA, along with compromised stations and the wireless medium using communicating timed automata which are the modeling language of the UPPAAL model checker. We proceed as well to the checking of some safety and liveness properties by means of this tool. We also propose stochastic models and we give some numerical results.

In this paper, we deal with failure detection in distributed systems under mobile environment constraints. For this effect, we propose a new protocol, called AFDAN (Accurate Fault Detection Protocol for Ad hoc Network), that is in charge of monitoring the distributed application against any node failure. The simulation results of our protocol show good performances in terms of accuracy and message overhead comparing to other protocols dedicated for MANETs.

In recent years, Delay Tolerant Networks (DTNs) have successfully presented as a possible extension of the Internet architecture in order to provide communication support to existing networks. However, these networks have a major issue which is the coordination among relays. In this work, we study the cooperative transmission for DTNs using coalitional game theory. We design a new incentive mechanism for heterogeneous system to induce coordination among DTN relays. In particular, we focus on the source packet dissemination to a destination using tow-hop relaying scheme, considering networks resource constraints: the relay buffer, the packet life time, and the energy consumption according to the mobile technologies. Rational mobiles are organized into separate coalition structures to meet a trade off between the source reward and the energy conservation. We discus the Nash equilibria for our game and the stable strategy state in which no mobile can get a higher payoff through changing unilaterally its coalition. Then, we use the distributed imitative Boltzmann-Gibbs learning algorithm enabling relays to learn the Nash equilibrium strategy; grand coalition. The improvement of the global system performance is examined, and a comparison between different inter-node collaboration states is presented.

Researchers have payed more and more attention on security issues in wireless networks this last decade as those networks are exposed to Denial of Service (DoS) attacks. Last improvements of the wireless technologies has developed the possibility to cars to communicate with Vehicular Ad Hoc networks more known as VANET. In these networks the impact of DoS is more important as it can affect the life of passengers. The features of DoS attacks are not well known in VANETs, thus we propose in this study a new Analytical model that represents the behavior of jamming attack in VANETS. This DoS attack consists of a node that disturb/disrupt the communications between nodes, then the overall quality of service is decreased. Representing this attack by analytical model using Markov chains is impossible as we face a problem of a state space explosion, thus we have used a more appropriate concept that is not usually used in the security in wireless networks with Stochastic Automata Networks. This model was used to calculate the rewards of this attack and can be used to decide whether a network is under or not a DoS attack.

Vehicular Ad hoc Networks (VANETs) aim to provide a high safety level to road users and enhance driving conditions for drivers. Thus, they are exposed to several kinds of attacks such as Denial Of Service attacks (DOS), especially the greedy behavior which affects services availability of authentic users. Greedy behavior attack has been well studied for Wireless local area networks (WLAN) and for Mobile Ad hoc Networks (MANETs). However, this attack is less studied for the case of VANETs. Indeed, the detection of a greedy behavior in quasi-static network is much easier than that in a network with low or high mobility. The aim of this paper is to detect greedy behavior in VANETs. More specifically, we propose a new detection algorithm based on a statistical method, linear regression and watchdog software. This algorithm distinguishes the existence or not of a greedy behavior and suspects the compromised nodes using a new appropriate defined metrics. The proposed algorithm is passive, it can be executed by any node in the network and does not require any modification of the IEEE 802.11p protocol.

LTE is becoming the most important radio access technology for mobile Networks, providing significantly a ubiquitous broadband access. This breakthrough brings strong QoS support, especially for multimedia services which are the most used applications in telecommunication. To reach its goals, LTE needs an appropriate packet scheduling scheme. This function is fundamental and very challenging, particularly in presence of multimedia services which require strict constraints on packet delay and packet loss. In this paper, we present an enhanced scheduling scheme which provides strict delay bounds and guarantees very low packet loss rate to multimedia services. This scheme is made of two levels that work in series and are designed to reach our goal. The performance of our proposed algorithm have been evaluated and compared to other schemes in the literature and simulations results demonstrated its effectiveness by showing that it optimized multimedia services performance and provided the best QoS support.

In this paper, we have proposed the IBE-RAOLSR and ECDSA-RAOLSR protocols for WMNs (Wireless Mesh Networks), which contributes to security routing protocols. We have implemented the IBE (Identity Based Encryption) and ECDSA (Elliptic Curve Digital Signature Algorithm) methods to secure messages in RAOLSR (Radio Aware Optimized Link State Routing), namely TC (Topology Control) and Hello messages. We then compare the ECDSA-based RAOLSR with IBE-based RAOLSR protocols. This study shows the great benefits of the IBE technique in securing RAOLSR protocol for WMNs. Through extensive ns-3 (Network Simulator-3) simulations, results have shown that the IBE-RAOLSR outperforms the ECDSA-RAOLSR in terms of overhead and delay. Simulation results show that the utilize of the IBE-based RAOLSR provides a greater level of security with light overhead.

The trend today is to access Internet through mobile devices, and people start using smartphones more than computers. This kind of services requires frequent updates through small messages from editors like in social networks. Although the use of such applications is subject to fees and consumes energy from limited batteries of smartphones. If a user activates his mobile device and has a useful contact opportunity with an access point, an update is received at the expense of monetary and energy costs. Thus, users face a tradeoff between such costs and their utilities. The goal of this paper is to show how a user can cope with such a tradeoff, by deriving a threshold policies. We consider the multi-user case, where each user try to maximize its reward based on a bonus given by the provider. We study the optimal policy in the Nash equilibrium. An optimal policy consists of deciding, based on the age of the last message received and the availability of access points whether to activate the mobile device or not. We model our problem using a POMDP with an average reward criterion. The accuracy of our model is illustrated through simulations.

We investigate energy conservation and system performance of decentralized resource allocation scheme in cognitive radio networks thoroughly based on secondary users competitive behavior. Indeed, the contention on data channel unoccupied by licensed user leads to a single winner, but also involves a loss of energy of all nodes. In this paper, we apply minority game (MG) to the most important phase from the opportunistic spectrum access (OSA) process: the sensing phase. We attempt to carry out a cooperation in a non-cooperative environment with no information exchange. We study the Nash equilibrium solution for pure and fully mixed strategies, and we use distributed learning algorithms enabling cognitive users to learn the Nash equilibrium. Finally, we provide numerical results to validate the proposed approach. The resource allocation based on minority game approach improves secondary users battery life and the performance of the network.

The use of sensor networks has increased rapidly over the last years. Due to their low resources, sensors come along with new issues regarding network security and energy consumption. Focusing on the network availability, previous studies proposed to protect the network against denial of service attacks with the use of traffic monitoring agents on some nodes. But if the control nodes go down or get compromised, they leave the network unprotected. To better fight against attacks, we try to enhance this solution by introducing an energy-aware and secure method to select these monitoring nodes (called cNodes) in a clustered wireless sensor network. Our election process is done in accordance to their remaining reserves: nodes with the higher residual energy are selected. We discuss limitations of this deterministic process concerning security and cluster coverage, and suggest as a workaround to designate new control nodes (called vNodes). Those vNodes are responsible for monitoring the cNodes by periodically enquiring about their remaining energy and ensuring that they do not lie during the election process (in attempt to keep their cNode role). Finally, we present some experimental results obtained with the ns-3 simulator in order to analyze the impact of our proposal on the energy repartition in the network.

One challenge of composite Web service architectures is the guarantee of the Quality of Service (QoS). Performance evaluation of these architectures is essential but complex due to synchronizations inside the orchestration of services. We propose in this paper, to use stochastic automata networks which a power formalism to modelize and to evaluate complex system with synchronizations.

In this paper we present a formal modeling and verification method of an enhanced version of the CSMA/CA protocol related to the IEEE 802.11 MAC layer, which has been proposed as the standard protocol for wireless local area networks (LANs). We deal mainly with the DCF procedure of this protocol throughout a sequence of transformation steps. We first use UML state machines to capture the behavior of wireless stations implementing the DCF and we thereafter translate them into the input language of the UPPAAL model checker, that is a network of communicating timed automata. Last, we proceed with the checking of some safety and liveness properties by means of this tool, such as deadlock-freedom.

To ensure connectivity in highly sparse Wireless Sensor Networks (WSNs), we consider a Ferry-assisted Wireless Sensor Network (FWSN). In our FWSN, message ferries moving along concentric annulus collect the static sensors generated packets and propagate them throughout a ferry-to-ferry forwarding schema to the sink. In this paper we present a queueing model to study and analyze the FWSN behavior. We will adapt a queuing model with finite queues which will allow us to analyze the network behavior in tens of packet loss using an analytic model. The objective of this work is to provide a way to optimize the energy consumption for each individual sensor. In our approach we consider a sensor Ferry, which is a mobile sensor with the capacity to provide the control operation upon the other fixed sensors within to network. Therefor, these fixed sensors will have to perform less control operations which will reduce their individual energy consumption. By doing so, this will automatically impact positively on to the lifetime of the network.

In this paper, we model a Virtual MIMO system using a game-theoretic approach. We are interested in the uplink, considering a non-coopertive game, where each user try to satisfy a quality of service. The uplink of a direct-sequence code division multiple access (DS-CDMA) data network is considered and a non-cooperative game is proposed in which users are allowed to choose their uplink receivers as well as to satisfy their quality of service. The utility function used in this framework is defined so that the throughput used by the user is divided into two components: the throughput received from cellular Network, and throughput received from Virtual MIMO System. In addition, this framework is used to study a constrained Nash equilibrium for the proposed game, and the impact of the interaction among users.

On a major security issue in WSN is the availability as these networks suffer from Denial of service Attacks. One of the most aggressive DoS attacks in WSN are greedy behaviors. This attack consists in increasing the bandwidth by a compromised node at the expenses of other nodes by not respecting the access network procedure. In this paper, we tackle the greedy behavior detection in the context of WSN using non slotted 802.15.4. Detecting of such attacks is not evident as it requires assessment tools that decide of a potential attack among normal network behaviors. Formal methods can be very useful to model and simulate the Network and therefore to provide a feedback of its behavior. We propose in this study to use Time Petri nets to detect greedy attaks. For this effect, we characterize the behavior of a greedy node, then we propose a modeling based on Time Petri nets for both a sane and a greedy node. Then we simulate the model under TINA platform by considering different scenarios and confront the obtained values of some parameters (as collision rate, the number of failings, and the energy consumption). Numerical results are used to detect misbehavior directly by nodes only by overhearing the transmissions.

Recent studies have shown that in LTE Uplink, the handshake procedure consisting of a scheduling request message from the User Equipment and a scheduling grant from the eNB required twice a communication over the air interface and caused notable delay. It could be harmful for loss and latency-sensitive applications such as Videotelephony traffics. So, we propose in this paper a new scheme which improves resource allocation for Videotelephony traffics and reduce the delay caused by Dynamic scheduling. The key idea is to schedule Videotelephony traffics using a Semi-Persistent strategy with Provisioning. The performance of our proposed algorithm have been evaluated in real LTE environments with LTE-Sim and simulations results demonstrated its effectiveness by showing that it optimized Videotelephony traffics performance and provided the best QoS support compared to the Dynamic Scheduling.

Vehicular Ad hoc Networks (VANETs) aim to enhance driving conditions and provide with drivers and road users a high level of safety. Thus, they are exposed to several kinds of attacks, especially Denial Of Service attacks family (DOS) which affect the availability of services of authentic users. In this paper, we define "Packets entropy" as a new metric to be used for VANETs denial of service attack detection. We propose also a new detection scheme for this effect. Using "Packets entropy", the proposed method is able to detect VANET DOS attacks by the supervision of traffic traces during short monitoring periods. It presents the advantage of rapidity, to be executed by any node of the VANET network and does not require any modification of the 802.11p MAC layer protocol used as a standard for VANETs. Simulations show the high efficiency of the newly defined metric and the related proposed detection method.

Multi-tenancy is the core feature that enables efficiency and cost effectiveness of cloud computing. However, it brings several new security concerns. Ensuring 'strong isolation' between co-localized tenants remains the most critical issue. This work aims at highlighting new attack strategies brought by the resource sharing paradigm in multi-tenant elastic IaaS Clouds in order to understand impacts of these attacks on the design of Intrusion Detection Systems in Cloud. The first part of this paper surveys the literature related to accepted vulnerabilities. Several Proofs of Concept are described and classified according to the results of the exploitation of these vulnerabilities. In the second part, we argue the existence of new attack strategies able to take advantage of the mechanisms which enable autonomic elasticity. These mechanisms are by nature sensitive to VMs resource consumption which can be easily manipulated by attacks. Finally, we give a representation of the presented vulnerabilities to engage a discussion on the limitations of pure user-centric security monitoring approaches for guaranteeing VM security.

Security of multi-tenancy in cloud platforms raises a growing interest since research has revealed that the sharing of resources constitutes a vector of vulnerability. In this paper, we examine how one can leverage the sharing of resources, through the manipulation of the amount of resources consumed by VMs, to abusively enforce the dynamic resource management system to trigger VM migrations. This causes waste of resources for the hosting infrastructure and affects performances of VMs. To demonstrate this cross-VM attack, we use VMware's Distributed Resource Scheduler (DRS) in charge of dynamic VM migration management. We perform a detailed analysis of the running of our experimentations by monitoring DRS details during the whole duration of the attack. We explore in various contexts the minimum amount of resources required for the attack to succeed. In our experimentation performed on small clusters, we observe higher vulnerability when the cluster gets larger and when DRS aggressiveness level gets higher. Finally, our experimentations show that the attack can be replayed several times to produce series of VM migrations.

Clustering algorithms play an important role in design and deployment of in wireless sensor networks (WSNs). We apply here a general clustering algorithm namely FFUCA (Fast and Flexible Unsupervised Clustering Algorithm) on WSNs. This application shows that FFUCA provides rapidly a strong organizational structure of nodes. We compare its built structures with those of the common algorithm LEACH to validate our approach. We aim to provide an optimal structure regarding energy consumption but with a low computational complexity.

In this paper, we consider a multimedia data transmission system over a wireless channel, where packets are queued at the transmitter. Multimedia data transmission over wireless networks often suffers from delay, jitter and packet loss. The main problem to implement a wireless network is the high and variable bit error rate in the radio link (fading, shadowing etc). Among the most important performance measures for real time applications are the packet loss probability. In order to improve the radio link, one often retransmits packets that have not been well received (using the Automatic Retransmission reQuest). This however may lead to queuing phenomena and increased delay due to retransmissions, and to losses of packets due to buffer overflow. In this paper, we allow that the number of retransmission is finite. We model the system state by a three-dimensional Markov chain which represents the evolution the radio link state, the number of packets in the buffer and the number of transmission of a packet in the service. We use an advanced approach based on the theory of singular perturbation in order to compute some performance of interest.

The ever-increasing number of customers and the need for higher data rates and multimedia services require the deployment of Small Cell Networks. In this paper, we propose a new computational approach to study performance and reliability of Small Cell Networks, taking into account the retrial phenomenon, the finite number of customers (mobiles) served in a cell and the random breakdowns of the base station channels, using the Generalized Stochastic Petri Nets (GSPNs) model as a support. However, one of the major drawbacks of this high-level formalism in performance evaluation of large networks is the state space explosion problem which increases when considering repeated calls and multiple unreliable channels. Hence, the novelty of this investigation is the presentation of an approach which allows a direct computing of the infinitesimal generator describing the customers behavior and channels allocation in as small cell, without generating nor storing the reachability set. In addition, we develop the formulas of the main stationary reliability and performance indices as a function of the network parameters, the stationary probabilities and independently of the reachability set markings.

Used in areas such as pollution measurement or data gathering over battlefields, wireless sensor networks have attracted more and more attention over the last years. The deployment of such a network is accompanied by several security issues, including data confidentiality. Robust encryption algorithms addressed to network communication exist, but they do not always match the low resources restrictions — low processor, memory, limited energy — set upon the sensors. To overcome this, other, simpler solutions have been proposed, such as the Securing Data based on Multi-Path routing method, or an application of the Shamir's Secret Sharing Scheme, which both use distinct paths in the network to send pieces of data obtained by splitting the original message. This paper addresses the two methods named above, and proposes a solution based on traffic classification, using alternatively the Securing Data based on Multi-Path routing method, the Shamir's Secret Sharing Scheme, and strong encryption algorithms.

Vehicular ad hoc network (VANET) is currently researched and achieved by several organizers to develop the intelligent transportation system (ITS). Research on Vehicular Ad hoc Network (VANET) has been conducting for long time. Nowadays, several organizers has obtained remarkable achievements contributing to the development of the Intelligent transportation system, ITS. The communication protocol in VANET named 802.11p protocol, has been improved to adapt to the high-speed environment. However, the communication among vehicles can be interfered even by Denial of Service (DoS) attacks such as jamming attacks. The vehicles communicate with each other in the high-speed environment. The time of data exchange between them must be extremely short. Solutions for detection of jamming attacks must occur quickly to detect more precisely. In order to detect jamming attacks more precisely, solutions therefore must occur very fast. In this paper, we propose one solution to detect jamming attacks. The following solution is based on the combination of the packet delivery ratio and its diminution.

WIth the facility of deployment, Wireless Sensor Networks becomes very popular but have special characteristics such as limited battery, limited processing power, and limited storage that makes the energy consumption saving a real challenge. Add to this and due to their distributed deployment, these networks are exposed to denial of service attacks such as jamming and greedy attacks. In all cases these attacks tackle the energy consumption in order to degrade the overall Quality of Service (QoS). In this paper, we propose an energy-preserving solution to detect compromised nodes in WSNs. The proposed method is based on hierarchical clustering technique which elect Controlled nodes (Cnode) that analyze the traffic inside a cluster and to send warnings to the cluster-head (CH) whenever an abnormal behavior is detected. The proposed method is dynamic as the Cnodes are periodically elected among ordinary nodes on each atomic cluster. Such a solution results in a better energy balance while maintaining good detection coverage as it is based on the distance between nodes, the output throughput and delay between packets transmission.

SUMMARY The IEEE P802.11s/D4.0 standard is not considered secure for the routing protocol. In this paper, we propose IBC‐HWMP, a secure Hybrid Wireless Mesh Protocol (HWMP) using identity‐based cryptography (IBC). The reason we use IBC is that it does not need to verify the authenticity of public keys. We have implemented the IBC mechanism to secure control messages in HWMP, namely path request and path reply. Our aim is to focus on secure data exchange in mutable fields. Through extensive ns‐3 simulations, results show that the overhead introduced by IBC‐HWMP is not significant compared with the classical HWMP and that, at the same time, we improve the security. Copyright © 2011 John Wiley & Sons, Ltd.

ABSTRACT Wireless mesh networks (WMNs) are one of the key technologies that will dominate wireless networking in the few years. The main characteristics of WMNs permit network connectivity anywhere anytime with simplicity and low cost. Their capability for self‐organization significantly reduces the complexity of network deployment. The draft standard of IEEE P802.11 s™/D4.0 is not considered secure for the routing protocol. In this paper, we propose a secure Hybrid‐Wireless‐Mesh Protocol using an Elliptic Curve Digital Signature Algorithm (ECDSA‐HWMP). We then compare the ECDSA‐based HWMP against identity‐based encryption (IBE)‐based HWMP. This study has been carried out to show the great benefits of the IBE technique in securing HWMP. Through extensive Network Simulator‐3 simulations, results have shown that the IBE‐HWMP outperforms the ECDSA‐HWMP in terms of overhead, throughput, loss ratio and delay. Simulation results show that the use of the IBE‐based HWMP provides a greater level of security with light overhead. Copyright © 2013 John Wiley & Sons, Ltd.

In this paper, we propose a security schema for the Radio Aware Optimized Link State Routing (RA-OLSR) protocol. We consider the security vulnerabilities for RA-OLSR and apply mechanisms based on Identity Based Encryption (IBE). The motivation behind using the IBE-signature is that it eliminates the need to verify the authenticity of public keys. We have implemented the IBE technique to secure messages in RA-OLSR, namely Hello and TC messages. Through simulation experiments, we have evaluated the performance of our IBE-RA-OLSR in terms of delay and control overhead. Simulation results show that the IBE-RA-OLSR does not induce a long overhead compared to the original RA-OLSR protocol.

Recent advances in localization technologies and algorithms for Wireless Sensor Networks (WSN) motivate the exploitation of location information in routing protocols. In this paper we consider the geographic forwarding of sporadically generated alarm messages. Our objective is to optimize sensor's energy consumption while respecting QoS constraints on transmission delay. For instance, we propose an optimal distributed relay selection policy for WSN with duty-cycling sensors based on a Markov Decision Process (MDP) with complete information. Also, we establish sufficient conditions for optimality of threshold policies. Then, end-to-end performances for a heuristic multi-hop relay selection strategy are established. Finally, we extend our model to account for queuing capabilities at sensor level.

A Wireless sensor Networks is a collection of simple devices with limited computation and resources. It is used to collect informations that are send back to the user. The sensed informations are real-time data streams for applications such as environmental monitoring, structural engineering, health care, VANET, and aircraft etc. The features of Wireless sensor networks (WSN) is that nodes are randomly deployed in the area where information collection is needed. Thus the security problem is an important issue as they are exposed to attacks and specifically to Denial of Service that can affect the sensor nodes battery lifetime. In this study, we propose and evaluate the performance of a secure routing protocol that take into account the existence of multipath between sender and destination to transmit data in several paths. The proposed protocol have been evaluated using stochastic automata networks formalism.

Wireless Mesh networks are a new way of deployment of wireless networks. They are based on radio nodes that directly communicate and are organized as a mesh topology. The new challenges of this type of deployment could be classified as: first, the improvement of the Quality of Service (QoS) to use the bandwidth more efficiently and to use different types of services; second, the security to avoid any intrusions or denial of service attacks. We shall focus on the la last point by proposing a new method in this study to secure Hybrid-Wireless-Mesh Protocol (HWMP) for Wireless-Mesh-Networks (WMNs) based on Watchdog. The purpose of using Watchdog is to prevent an attack on the internal nodes and to exclude them from network operations. We have implemented the Watchdog technique in order to secure data exchange in mutable fields. Through extensive ns-3 simulations, the Watchdog-HWMP is able to detect both malicious attacks and selfish behaviors without significant overhead.

In recent years, many approaches and techniques have been explored for the optimization of energy usage in Wireless Sensor Networks (WSN). It is well recognized that a proper energy consumption model is the foundation for developing and evaluating a power management scheme in WSN. In this paper, we propose a new complete information Markov Decision Process (MDP) model to characterize sensors energy levels. We also propose and compare several centralized power control policies to select the more efficient policy that optimizes throughput and energy consumption.

The idea to allow unlicensed users to utilize licensed bands whenever it would not cause any interference is one of the fundaments of cognitive radio. In this paper we propose some allocation channel strategies to provide more QoS for unlicensed users. We assume that one channel is dedicated for unlicensed users that can eventually use licensed users channels if idle. The first allocation channel strategy reconsiders, in case of unavailable licensed users's channels, the request of unlicensed users to be processed by the dedicated channel. The second strategy doesn't reconsider it and simply reject it. QoS performances of the two patterns are evaluated and discussed using analytical models and simulations. For the first communication strategy, we based our model on the work of Habachi and Hayel which we enhance. We proceed to some corrections of mathematical and formulations errors. Analytical and simulation results show that the performances offered by the primary channels to secondary user are better than performances offered by the dedicated channel, however, the performance offered by the primary channels are negatively impacted by the cost of sensing.

In this paper we have implemented the Hash technique to provide security in HWMP (Hybrid Wireless Mesh Protocol). Then after, we compared the Hash based HWMP against IBC (Identity Based Cryptography) based HWMP. This study has been carried out to show the great benefits of the IBC technique in securing HWMP. Results have shown that, IBC-HWMP outperforms the hash-based HWMP in terms of overhead and delay. According to the obtained results the use of IBC with HWMP provides a greate level of security with light overhead.

Recently, the directional antenna has received intensive research due to its variety of potential benefits for wireless communication systems, especially in the context of ad hoc networks. Nodes equipped with this type of antennas can communicate simultaneously without interference, and potentially establish links between them with less routing hops. This interference reduction provide a higher channel reuse leading to better resource exploitation and potentially better performance. In this study we want to take the advantage of directional antennas by proposing a sectorial coverage in a deployment of a WMN backbone based on mesh mode. Mainly, we propose a new architecture based on this type of antennas and OLSR protocol is used as routing protocol. We show by simulations under NS3 that the proposed architecture improve the overall QoS. We propose also an implementation of this type of antennas and we show with numerical results that the use of directional coverage outperform the omnidirectional coverage.

In this paper, we propose a security mechanisms for the Hybrid-Wireless-Mesh Protocol (HWMP). Our mechanisms is based on the Identity Based Crytography. The motivation behind using IBC is that it eliminates the need to verify the authenticity of public keys. We have implemented the IBC technique to secure control message in HWMP, namely RREQ and RREP. In these Control messages, we interested only by the mutable fields (i.e. fields that an changing during control packet exchange). Throuhg simulation, we have evaluted the performance of our security mechanism in terms of control overhead, and does not induce too much overhead compared to the original HWMP (i.e. without security).

This paper tackle the problem of coverage in IEEE 802.11 in mesh mode. Instead of omnidirectional coverage, we propose to use directional coverage that can increase the distance between the nodes. The use of directional antenna have two main advantages. The first is to increase the performance of QoS of considered services. The second is that using directional antenna allows to improve the spatial reuse of the wireless channel, which allows nodes to communicate simultaneously without interference, and potentially establish links between nodes far away from each other, and the number of routing hops can be fewer than that of omnidirectional antennas. We also propose an new amendment to reduce the routing overhead related to the use of multiple interfaces. We have evaluated the performance of the proposed architecture and we show with numerical results that the use of directional coverage outperform the omnidirectional coverage.

In this paper we present an energy efficient priority based MAC protocol for Wireless Sensor Networks (WSNs). We abbreviate it as PRIMA. The PRIMA protocol consists of two phases; a clustering phase and a channel access phase. Clustering the senor network makes the MAC protocol to handle well network scalability issues. The channel access is composed of a hybrid mode of TDMA and CSMA. CSMA mode is used to communicate control messages, while data messages are assigned TDMA slots. Doing so, minimizes packet collisions and consequently minimizing energy consumption. Our PRIMA protocol forces the nodes that have no data to send to go early into a sleep state to save energy, this minimizes the idle listening periods which is considered as a main source of the energy consumption in sensor networks. The PRIMA protocol provides Quality of Service (QoS) by employing a queueing model to classify the traffic depending on its importance into four different queues. Higher priority queues have absolute preferential treatment over low priority queues. Through simulations and analytical analysis, we evaluate the performance of our proposed MAC protocol and compare it against the Q-MAC protocol. Results have shown that our protocol outperforms Q-MAC in terms of energy consumption, packet delivery ratio and average packet delay.

Wireless Sensor Networks lifetime mainly depends on energy saving efficiency. In this paper, we propose an energy-efficient self-stabilizing topology control protocol for WSN. We reduce the transmission power of each node so as to maintain network connectivity while saving maximum energy. Besides, we propose an approximation algorithm for minimum weighted connected dominating set that builds a virtual backbone formed by sensors with maximum energy. This backbone is used for efficient routing purpose. Through our simulation results, we show the efficiency of our proposed algorithm.

In this paper we have implemented the ECDSA (Elliptic Curve Digital Signature Algorithm) technique to provide security in HWMP (Hybrid Wireless Mesh Protocol). The motivation behind the use of ECDSA is that it is integrated into the IEEE P802.11s/D4.0 standard. We have used the ECDSA technique to secure control message in HWMP, namely PREQ (Path Request) and PREP (Path Reply). In these Control messages, we are interested only by mutable fields (i.e. fields that change during control packet exchange). Simulation results show that the ECDSA-HWMP does not too much a long overhead compared to the original HWMP.

WIMAX networks are aim to provide services with high throughput (up to 70 Mbps) and with a large coverage (up to 50 Km) To ensure QoS architecture has been designed and in the IEEE 802.16.e amendment they introduce the service differentiation by 4 service classes (UGS, rtPS, nrtPS and BE). Add to this an Admission control (AC) has been specified to avoid any degradation of the active connection. This mechanism is not defined in the literature and is let to the operators. Major implemented AC use the strict priority. The drawback of the strict priority is that it penalizes service classes with the lowest priority especially the BE. In this paper we propose to improve the AC of BE in WIMAX networks. To achieve this goal we propose to use the leaky bucket for both rtPS an nrtPS in order to reduce lightly the number of accepted connections and to improve considerably the number of BE accepted connection. We evaluate the performance of the proposed scheme by a markovian model.

Wireless mesh network (WMNs) are an emerging technology, presented mainly as a way to build a multi-hop network based on an infrastructure. IEEE has developed a draft 802.11s describing the enhancement of the IEEE 802.11 for mesh networks. This new standard aims to create a new wireless configuration that manages the topology, the quality of radio link and the routing. For routing, two path selection protocols HWMP (Hybrid Wireless Mesh Protocol) and RA-OLSR (Radio-Aware Optimized Link State Routing) are considered. The both routing protocols are inadequate for multimedia applications, such as video conferencing, which is often requiring guaranteed Quality of Service (QoS). QoS routing requires not only finding a best route from a source to a destination according to some criteria (like AirTime metric, hop numbers, etc.) , which is the case of HWMP, but a route that satisfies the end-to-end QoS requirement, often given in terms of bandwidth or delay. This paper tackles this last point by improving the HWMP protocol that handles QoS for real time applications. The goal of the proposed enhancement is to increase the bandwidth utilization and to avoid any network congestions. The method is based on the evaluation of QoS parameters as end-to-end delay or remaining bandwidth and to determine if they can fit with the real time application. Simulation results show that the proposed solution outperform classical HWMP.

In large scale networks like the IEEE 802.16 (WiMAX), monitoring the amount of traffic within the network is an important task. By controlling the amount of network traffic, congestion can be largely decreased. Therefore, the fulfilment of Quality of Service (QoS) requirement for each traffic classis guaranteed. In this study we propose a traffic policer based on token bucket concept for WiMAX. Token bucket parameters (token rate and bucket size) are adjusted according to the traffic characteristics of each traffic class individually. Simulation results show that our traffic policing technique greatly enhances network performance. It decreases the average delay for real time traffic like rtPS, and by consequence reduces data drop probability due to missed deadlines. It also decreases data loss probability for non real time service class like nrtPS.

This paper presents an energy efficient multipath routing protocol specifically designed for wireless sensor networks (referred as RELAX). RELAX protocol tries to utilize the relaxation phenomenon of certain batteries to increase the battery lifetime and hence increasing the overall lifetime of the sensor network. Relaxation periods enable the battery to recover a portion of its lost power; it has been proven that the intermittent operation of some alkaline batteries increases its lifespan by about 28%. RELAX uses a link cost function that depends on current residual energy, available buffer size, and link quality (in terms of Signal-to-Noise ratio) to predict the best next hop during the path construction phase. RELAX routes data across multiple paths to balance the energy consumed across multiple nodes and to increase the throughput as well as minimizing packet end-to-end delay. Before transmitting the data, RELAX protocol adds data redundancy through a light weight Forward Error Correction (FEC) technique to increase the protocol reliability and resiliency to path failures. Many simulation experiments have been cried out to evaluate the protocol performance. Results show that RELAX protocol achieves lower energy consumption, lower packet delay, higher throughput, and long node lifetime duration compared to other protocols.

The most widely used standard for wireless networks is the IEEE 802.11. In 802.11, dense deployment of Access Points (APs) is needed to meet customers' demands. The installation of multiple access points is expensive and not convenient because of Ethernet wiring from access points to backhaul network access modem, hub, etc. Wireless mesh network (WMN) is an emerging technology; presented mainly as the solution to the problem related to the necessity to create a wireless distribution system (APs need to interconnect wirelessly). It is expected to replace the wireline infrastructure network due to the scalability and rapid cost effective deployment and maintenance. One of the WMN applications is that they can be used as a backbone. The characteristics of self-organization and auto-configuration in the wireless mesh backbone offer many benefits such as low upfront investment, increased reliability and scalability. In this Paper, we are interested, to the using of directional antennas in wireless mesh backbone. By using this kind of antenna in wireless mesh backbone we can improve the performance and QoS. The directional antenna allow to improve the spatial reuse of the wireless channel, which allows nodes to communicate simultaneously without interference, and potentially establish links between nodes far away from each other, and the number of routing hops can be fewer than that of omnidirectional antennas. We also propose a new amendment to reduce the routing overhead related to the use of multiple interfaces.

Mobile Ad hoc Networks (MANETs) are formed by collection of, potentially mobile, portable devices without established infrastructure. In such networks, connectivity is established through IP addresses and dynamic routing. MANETs are highly dynamic with frequent nodes joining and departure. Due to this node dynamicity, the node's IP address changes frequently. Therefore, to enable and run common user applications (e.g. web browsing and email) on such networks, the use of well known names that are unique and easy to remember is required. Thus a name resolution mechanism which maps names to their corresponding IP addresses has become necessary. Due to the lack of a centralized infrastructure, supporting naming resolution and address configuration becomes a difficult task and the use of the traditional DNS system becomes impossible in such networks. Therefore, in this paper, we propose a distributed naming system based on the peer-to-peer Chord protocol which provides naming resolution in the presence of mobility and node failures. Using P2PSIM simulator, we evaluate the proposed naming scheme. Simulation Results demonstrate the effectiveness of our proposal.

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Abstract Enabling quality of service (QoS) applications over battery‐constrained wireless sensor networks (WSNs) poses significant challenges, because of the special characteristics of such networks. Developing real‐time applications for WSNs necessitates the development of new communication protocols capable of achieving application‐specific QoS and at the same time save energy. In this paper, we continue our previous work on developing and improving our EQ‐MAC protocol, which is designed specifically for WSNs to reduce energy consumption and provides QoS guarantees through the use of the service differentiation concept. The proposed protocol consists of two subprotocols: Classifier MAC (C‐MAC) and Channel Access MAC (CA‐MAC). C‐MAC is responsible of classifying gathered data at sensor nodes based on its importance. The CA‐MAC is an energy conserving medium access mechanism which uses a hybrid scheduling technique. CA‐MAC saves energy by differentiating between control and data messages. Data messages are assigned scheduled slots with no contention (here we have to emphasize that slots are assigned only to those nodes that have data to send, this allows an efficient energy use of the Time Division Multiple Access (TDMA) slots), whereas short periodic control messages are assigned random access slots. To study the performance of the EQ‐MAC protocol, we have conducted several simulation experiments on Network Simulator (NS‐2) to evaluate and compare the performance of our protocol against S‐MAC and Q‐MAC protocols. Simulation results demonstrate that EQ‐MAC outperforms the other two protocols and achieves a significant improvement in terms of the energy expenditure and delivery ratio. Under prioritized traffic, EQ‐MAC is comparable to Q‐MAC in average latency, while achieving less energy consumption. Copyright © 2010 John Wiley & Sons, Ltd.

Due to their nature, vehicular ad hoc network (VANET) is vulnerable to denial of service (DoS) attacks, such as jamming attack. The objective of a jammer is to interfere with legitimate wireless communications, and to degrade the overall QoS of the network. In this paper, we propose a model to detect a particular class of jamming attack, in which the jammer transmits only when valid radio activity is signaled from its radio hardware. This detection model is based upon the measurement of error distribution.

Wireless Sensor Networks (WSNs) are subject to node failures because of energy constraints, as well nodes can be added to or removed from the network upon application demands, resulting in unpredictable topology changes. Furthermore, due to limited transmission range of wireless sensor nodes, multiple hops are usually needed for a node to exchange information with other nodes or sink node(s). This makes the design of routing protocols in such networks a challenging task. In all proposed single path routing schemes a periodic low-rate flooding of data is required to recover from path failures, which causes consumption of scarce resources of the sensor node. Thus multipath routing schemes is an optimal alternative to maximize the network lifetime. Multipath routing schemes distribute the traffic across multiple paths instead of routing all the traffic along a single path, which spreads consumed energy evenly across the nodes within the network, potentially resulting in longer lifetimes. In this paper, we propose a robust and energy efficient multipath routing protocol (shortly abbreviated as REER). REER uses the residual energy, node available buffer size, and Signal-to-Noise Ratio (SNR) to predict the best next hop through the paths construction phase. REER examines two methods of traffic allocation; the first method uses a single path among the discovered paths to transfer the data message, when this path cost falls bellow a certain threshold, it then switches to the next alternative path. The second method is to split up the transmitted message into number of segments of equal size, add XOR-based error correction codes, and then transmit it across multiple paths simultaneously to increase the probability that an essential portion of the packet is received at the destination without incurring excessive delay. Through computer simulation, we evaluate and study the performance of our routing protocol and compare it with other protocols. Simulation results show that our protocol achieves more energy savings, lower average delay and higher packet delivery ratio than other protocols.

Mobile ad hoc networks are a new wireless networking paradigm for mobile hosts. Unlike traditional mobile wireless networks, ad hoc networks do not rely on any fixed infrastructure. Instead, hosts rely on each other to keep the network connected. The military tactical and other security- sensitive operations are still the main applications of ad hoc networks. One main challenge in design of these networks is their vulnerability to Denial-of-Service (DoS) attacks. In this paper, we consider a particular class of DoS attacks called Jamming. The objective of a jammer is to interfere with legitimate wireless communications. A jammer can achieve this goal by either preventing a real traffic source from sending out a packet, or by preventing the reception of legitimate packets. We propose in this study a new method of detection of such attack by the measurement of error distribution.

The CSMA/CA protocol is well known to handle the channel access to various users in wireless ad hoc networks using IEEE 802.11 technology. This protocol requires nodes to wait for some time before initiating a transmission to avoid collisions. As a result, the greedy behavior of some misbehaving nodes can try to lower their waiting time in order to access the channel earlier and penalize the other nodes. In order to avoid this misbehavior, we propose in this paper a model based on measuring the linear regression of nodes' access time to the channel. We have demonstrated that this model exhibits a linear regression between the different nodes' access time. This result has been also confirmed by simulations. In this model, each deviation from the estimated slope is considered as a source of cheating from a corresponding node. By using this detection model, we were able to detect most of the misbehaving nodes in wireless ad hoc networks without requiring modifications to the IEEE 802.11 MAC protocol.

The emergence and success of IP networks make the development of new services like voice, multimedia or web services possible. One of the major problem of these type of application is that IP networks is not designed to provide Quality of Service (QoS) in an end to end architecture. Thus the performance evaluation of these applications is important to guarantee a high level of QoS. We focus in this study to evaluate the performance evaluation of Web services which is the most difficult to achieve because of the complexity of their architectures. The classical mathematical formalisms such as queueing networks can not be used in this kind of problems due the synchronization events and the state space explosion. In this paper we propose to use an adequate and efficient modelling tool: the Stochastic Automata Network (SAN) to evaluate the performance of Web services architecture over IP networks. Numerical results using PEPS are given for considered performance measures.

Mobility together with energy efficiency in wireless sensor networks have imposed significant challenges for the medium access control (MAC) protocol design to provide reliable communication with good data rates and low energy consumption. Most of the MAC protocols proposed for wireless sensor networks assume static sensor nodes, which usually causes degradation in network performance in scenarios involving mobile sensors. In this paper, we introduce a mobility aware and energy efficient medium access protocol (shortly abbreviated as MEMAC) for mobile wireless sensor networks. Our MEMAC is based on a hybrid scheme of TDMA and CSMA that informs sensor nodes when to wakeup or when to go to sleep to save energy. Furthermore, MEMAC protocol dynamically adjusts the frame size to enable the protocol to effectively adapt itself to changes in mobility and traffic conditions. Through computer simulations, we evaluate the performance of the MEMAC and compare it against the MMAC protocol. Simulation results have shown that MEMAC outperforms MMAC in terms of energy consumption, packet delivery ratio and average packet delay.

Mobile ad hoc networks (MANETs) are dynamic mobile networks that can be formed in the absence of any pre-existing communication infrastructure. MANETs are vulnerable to jamming attack due to their salient characteristics. The objective of a jammer is to interfere with legitimate wireless communications, and to degrade the overall QoS of the network. In this paper, we propose a new method to react at jamming attacks. The military has long dealt with jamming by using frequency-hopping spread spectrum communication. Unlike frequency hopping that takes place at the PHY layer, our purpose takes place at the MAC layer.

Welcome to the WLN 2009, taking place in Zurich, Switzerland!

Enabling real time applications in Wireless Sensor Networks (WSNs) demands certain delay and bandwidth requirements which pose more challenges in the design of networking protocols. Therefore, enabling such applications in this type of networks requires energy and Quality of Service (QoS) awareness in different layers of the protocol stack. In many of these applications (such as multimedia applications, or real time and mission critical applications), the network traffic is mixed of delay sensitive and reliability demanding data. Hence, QoS routing becomes an important issue. In this paper, we propose an Energy Efficient and QoS aware multipath routing protocol (we name it shortly as EQSR) that maximizes the network lifetime through balancing energy consumption across multiple nodes, uses the concept of service differentiation to allow high important traffic (or delay sensitive traffic) to reach the sink node within an acceptable delay, reduces the end to end delay through spreading out the traffic across multiple paths, and increases the throughput through introducing data redundancy. EQSR uses the residual energy, node available buffer size, and Signal-to-Noise Ratio (SNR) to predict the best next hop through the paths construction phase. Based on the concept of service differentiation the EQSR protocol employs a queuing model to handle both real time and non-real time traffic. By means of computer simulations, we evaluated and studied the performance of our routing protocol and compared it with another protocol. Simulation results have shown that our protocol achieves lower average delay and higher packet delivery ratio than the other protocol.

Abstract Power management is an important issue in wireless sensor networks (WSNs) because wireless sensor nodes are usually battery powered, and an efficient use of the available battery power becomes an important concern specially for those applications where the system is expected to operate for long durations. This necessity for energy efficient operation of a WSN has prompted the development of new protocols in all layers of the communication stack. Provided that, the radio transceiver is the most power consuming component of a typical sensor node, large gains can be achieved at the link layer where the medium access control (MAC) protocol controls the usage of the radio transceiver unit. MAC protocols for sensor networks differ greatly from typical wireless networks access protocols in many issues. MAC protocols for sensor networks must have built‐in power conservation, mobility management, and failure recovery strategies. Furthermore, sensor MAC protocols should make performance trade‐off between latency and throughput for a reduction in energy consumption to maximize the lifetime of the network. This is in general achieved through duty cycling the radio transceiver. Many MAC protocols with different objectives were proposed for wireless sensor networks in the literature. Most of these protocols take into account the energy efficiency as a main objective. There is much more innovative work should be done at the MAC layer to address the hard unsolved problems. In this paper, we first outline and discuss the specific requirements and design trade‐offs of a typical wireless sensor MAC protocol by describing the properties of WSN that affect the design of MAC layer protocols. Then, a typical collection of wireless sensor MAC protocols presented in the literature are surveyed, classified, and described emphasizing their advantages and disadvantages whenever possible. Finally, we present research directions and identify open issues for future medium access research. Copyright © 2009 John Wiley & Sons, Ltd.

It is well known that TCP protocol behaves quiet loosely in mobile wireless environments. In fact, when a mobile host moves from one IP domain to another it has to get a new IP address in the new domain. This process of getting a new IP address should be automatic and fast enough in order to keep active any running TCP session without loosing the quality of service provided to the user. Mobile IP has been developed to manage the user mobility in mobile wireless networks. However, this protocol is not well suited to support a TCP handoffs during the node's handover process which will help in keeping active any running TCP sessions. In this paper, we have designed a new management architecture which will ensure the continuity of any TCP connection when a mobile host executes a handover. In order to validate our architecture, we have evaluated its performance by adopting an analytical model.

In this paper, we propose a new scheme to detect misbehaving nodes that violate their contracted bit rate in the context of wireless ad-hoc networks. To achieve this, we use our DCF-MB access policy instead of the well known DCF protocol. The DCF-MB approach ensures a fair time occupancy of the shared channel among competing nodes. Using our DCF- MB access scheme, we derive analytically the expected useful occupation ratio of the channel when all the nodes respect their contracts. This value is used as a reference to detect misbehaviors inside the network. We show through simulations the efficiency of our proposal that ensures fair bandwidth sharing, enabling thus the detection of misbehaving nodes. We also evaluate through simulations and analytic analysis the effectiveness of the system in estimating the useful channel occupation and improving the network performance.

In this paper we propose an efficient multi-service scheduling scheme called real-time adaptive scheduler (RTAS) for WiMAX service classes. It is based on deficit round robin with an adaptive quantum according to the QoS requirement of each considered service. Our scheduler assures fairness between the different class of services on either uplink or downlink TDD frame. Simulation results show the achieved fairness and the adaptation with real-time characteristics of data traffic.

In this paper, we present a new MAC layer protocol for wireless sensor networks that reduces energy consumption and provides Quality of Service (QoS) guarantees through the use of service differentiation concept. The proposed protocol (named as EQ-MAC) consists of two sub-protocols: Classifier MAC (C-MAC), and Channel Access MAC (CA-MAC). C-MAC is responsible of classifying gathered data at sensor nodes based on its importance and then stores it in the appropriate queue of the node's queuing system. The CA-MAC is an energy efficient medium access mechanism that uses a hybrid approach of both scheduled and unscheduled schemes to gain a save in energy, and hence prolonging the network's lifetime. The save in energy achieved by CA-MAC is coming from the differentiation between control and data messages. Data messages are assigned scheduled slots with no contention (here we have to emphasize that slots are assigned only to those nodes which have data to send, this allows an efficient energy use of the TDMA slots), while short periodic control messages are assigned random access slots. To study the performance of the EQ-MAC protocol, several simulation experiments were conducted. EQ-MAC is compared with both Q-MAC and S-MAC protocols. Simulation results demonstrate that EQ-MAC outperforms the other two protocols and achieves a significant improvement in terms of energy expenditure. Under prioritized traffic, EQ-MAC is comparable to Q-MAC in average latency, while achieving less energy consumption.

IEEE 802.16 standard provides a broadband wireless access solution. WiMAX (Worldwide interpretability for microwave access) is the business definition of the 802.16-2004 amendment. In WiMAX, quality of service (QoS) is provided through both classification and scheduling of the four different types of traffic classes defined by the standard. Each class has it own bandwidth requirements as well as its level of QoS, which has to be maintained. In this paper, we provide a performance analysis of three types of connections defined in the standard (UGS, rtPS, nrtPS). Different levels of priority and blocking probability are assigned to each class of service. This performance analysis has been done using an analytical model for evaluating admission control (AC) for the previous mentioned classes in WiMAX network.

Recently, many QoS architectures have been proposed to handle efficiently multi-service flows in IEEE 802.16 networks. However, these architectures have several weaknesses as they present some scalability issues and donpsilat consider the wireless nature of such networks (e.g. variable link capacity). Moreover, the proposed approaches fail in providing efficient admission control (AC) procedure to tackle congestions at both uplink and downlink channels. In this paper, we introduce new modules in both subscriber station (SS) and base station (BS), allowing more efficient handling of multi-service flows. We particularly focus on the design of a probabilistic and self-configuring AC algorithm, which prevents from uplink and downlink congestions while guaranteeing QoS to rtPS and nrtPS flows. Simulation results show that the proposed admission control protocol highly improves the management of underlying wireless resources, allowing therefore network operators to accept more QoS-enabled services.

WiMAX (worldwide interpretability for microwave access) is one of the leader standards of broadband wireless access (BWA). This standard becomes a competitor of 4G or LTE (long term evolution) with the introduction of different class of service flow (UGS, rtPS, nrtPS, BE). Each service class has its own QoS requirements. Even if the standard specify the transmission policy of each service class, it recommends the implementation of an admission control (AC) without any specification. As the standard does not define any specifications for the AC, then this task is left for the operator. In this paper, we propose an implementation of an AC algorithm mechanism for IEEE 802.16. The performance evaluation of these networks by analytical models is not easy due to the state space explosion, thus we use the stochastic automata networks (SAN) formalism to model our proposed AC mechanism. With SAN we calculate the rewards of the proposed AC and we show that the proposed solution is efficient.

The domain name system (DNS) is a cornerstone for the Internet and the most globally deployed Internet service that provides user-friendly naming for Internet hosts. DNS is a distributed data base that allows convenient storing and retrieving of resource records. Recently an interesting feature was added to BIND implementation of the DNS system to support secure dynamic updates. In this paper, we use the DNS and its ability to support dynamic updates to propose a mobility solution that locates and tracks mobile hosts while they change there points of attachment (IP addresses) in the network. The main objectives of this paper is to study and re-evaluate the DNS system with respect to dynamic updating protocol and provide a performance study to determine the ability of the DNS to support mobility and real time services. The experimental results have shown that updating speeds (i.e. propagation of updates along the system) are fast enough for the DNS to provide real time services, and we can conclude that the conventional DNS system with the dynamic updating feature can be used in a macro mobility handling scheme.

A particularly severe attack on routing protocols in ad hoc networks is the so-called wormhole attack in which two or more colluding attacking nodes record packets at one location, and tunnel them to another location for a replay at that remote location. When this attack targets specifically routing control packets, the nodes that are close to the attackers are in effect shielded from finding any alternative routes to the remote location with more than one or two hops, and thus all the routes will be directed to the wormhole established by the attackers. In optimized link state routing protocol (OLSR), if a wormhole attack is launched during the propagation of link state packets, the wrong link information will propagate throughout the network, leading to routing disruption. In this paper, we devise an efficient method to detect wormhole attacks in the OLSR protocol. This method tries to ascertain the effective presence of neighbors by employing an efficient neighborhood detection algorithm. Our method has several advantages since it does not require any time synchronization or location information and shows high detection rate under various scenarios.

Due to its increasingly growing capacity, WLANs are becoming mature enough to be integrated in a real commercial multi-service offers. However, their success will mainly depend on their ability to provide quality of service for different media types (audio, video, etc.). In this paper, we devise a new protocol which provides a more strict service differentiation between different traffics. The protocol deals also with the well known 802.11 anomaly and improves network throughput by using separate contention window ranges reinforced by a packet length differentiation. Thus, each flow will be seen allocated a selected backoff interval and a packet length from variable bounded ranges to improve both throughput and delay. The different backoffs and packet lengths vary dynamically depending on the propagation conditions. Fairness is then taken into consideration as the adaptation is made sensitive to upper-layers' quality of service metrics as well as to the propagation conditions observed at the PHY layer expressed with SNR value, carrying out a cross- layer architecture.

In this paper, we propose a new solution to cope with the unfairness limitations of the distributed coordination function (DCF) algorithm. Our solution is based on multiple backoff windows principle. We demonstrate through simulations the efficiency of our proposal that enables fair bandwidth sharing and increase total network throughput.

TCP is a protocol which performs well with networks that are physically linked and hosts are stationary. To establish a TCP connection, one must associate an IP address with a port number for both sender and receiver. However, in wireless environments mobile hosts are subject to change their attachment point during communication, this process is called handoff. Thus, in mobile environments the TCP operation is more complicated, because the mobile moves from one cell to another and it changes of network’s domain, then it acquires a new temporary IP address. Hence, the TCP packet loss is increased. Mobile IP was developed to manage the user mobility in wireless networks. However, this protocol is not adapted to support TCP session throughout the handover process. In this study, we have modeled the proposed architecture which ensures the continuity of TCP connection when a mobile executes a handover. We have evaluated the performance of the architecture by an analytical model.

International audience

Summary form only given. Due to random access in wireless networks using CSMA/CA like in Wifi networks, the integration of services with a lot of quality of service needs is impossible. In this paper, we propose to study and to evaluate a new MAC protocol that takes into account different types of traffic (e.g.. voice and data) and for each traffic, different priority levels are considered. To improve the QoS of WIFI MAC protocols, we add a selective reject and push-out mechanisms. To model our protocol, using Markov chain is impossible because it provides Markov chain with a large state-space. This is due to the resource management and user mobility. Thus, we propose to build an aggregated Markov chain with a less state-space that allows to compute easily performance measures. We have used stochastic comparisons of Markov chains to prove that the considered access protocol (with selective reject and push-out mechanisms) gives less loss rates of high priority connections (data and voices) than the traditional one (without selective reject and push-out mechanisms). We give numerical results to confirm mathematical proofs.

Summary form only given. VHE (virtual home environment) poses new challenges in terms of services customization and the integration of end-to-end QoS management. Our approach provides a model for the mobility management in IPv6 according to VHE context. In this paper we introduce an architecture which guarantees authorized user access and user mobility management. The mechanism used for user authentication is based on LDAP (lightweight directory access protocol) and RADIUS (remote access dial in user service) services, giving accurate localization of the mobile node even in the presence of hadover; at this point, the user must be re-authenticated and consequently the VHE services are activated to transport the user profile to the foreign network.

The fourth generation wireless network represents the next generation of mobile networks. These networks include ad-hoc networks that are characterized as autonomous and independent of any existing infrastructure. One of the major problems of these networks is the security of data and equipment. Data should be confidential, and the equipments should also be protected for saving energy, or for isolation of a congestioned node, etc. In this study we propose a new protocol SERAN (security equipment protocol in routing in ad hoc networks), which permits to hide an equipment in ad hoc networks.

In this paper, we introduce a solution for securing data in ad hoc networks. We exploit the existence of multiple paths between nodes in an ad hoc network to increase the robustness of transmitted data confidentiality. In ad hoc networks, security depends on several parameters and reaching a good security degree is a hard task. Recently, there are several proposed solutions treating authentication, availability, secure routing and intrusion detection etc, in ad hoc networks. An overview of some current solutions, implementation details and experimental results are discussed in this paper.

Mechanisms for security and quality of service (QoS) used in fixed networks cannot be adapted for mobile networks. The mobility of users makes problems in authentication and QoS conservation during handoffs. We focus on the management of security and QoS for user mobility. We propose an authentication architecture which uses a network management protocol (common open policy services) standardized by the Internet Engineering Task Force and extensible authentication protocol on a smart card to perform authentication over the wireless network.

Due to the inherent quality of wireless mobile networks and the lack of center control units, the security is always a weak point for ad hoc networks. We propose a new concept, that is, the security equipment in ad hoc networks. We consider that a user can use an infrastructure ad hoc without completely putting his resources to the network. He can become invisible at the routing level without loss his abilities of receiving and sending. Thus he well be protected at the equipment level.

New services are introduced in the broadband network such video or multimedia. These services have some quality of service constraint such as transit delay, and cell loss probability. To improve the quality of service, it is important to optimize the bandwidth utilization. In this study we focus on this problem, and our major contribution is to provide quality of service by the development of a new rerouting algorithm. All existing routing algorithms optimize at the time of call establishment. The originality of our contribution is to optimize routing before and after call establishment. To show the benefit of our algorithm we do a performance evaluation using a new technique called SAN (stochastic automata networks), which is adapted to our problem.

To provide a service continuation from fixed broadband networks to the wireless part, new frequencies are allocated to increase the system capacity. Whereas the reuse partitioning is not adapted to those new needs, the multi-tier cell concept appears to be a good solution. We propose a new bandwidth allocation policy for a multi-tier cellular network which optimizes bandwidth utilization for customers, denoted MAHCN (multiservice allocation in hierarchical cellular networks). Our new protocol considers the service requirements based on two criteria: the mobile speed (low or high) and the type of request (voice or data).