In Vehicular Ad-hoc Networks (VANETs) and major transportation systems, efficient communication protocol is vital for timely data transmission to vehicles. The dense vehicular network poses challenges to efficient channel-sharing. For the proper utilization of the available bandwidth, optimization of channel mechanisms is crucial. The proposed approach enables vehicles to dynamically tune their Contention Windows (CWs) using locally observable MAC-layer information, with the objective of jointly maximizing throughput, minimizing delay, and maintaining fair channel access. Comprehensive simulations and analysis show notable improvement in the overall network efficiency in terms of throughput, collision, and delay. The adaptiveness of the proposed algorithm guarantees flexibility to changing traffic conditions and is well-suited to the evolving Intelligent Transportation Systems (ITS). With an emphasis on high throughput, low latency, and fair channel allocation, the proposed model contributes to the advanced communication protocols for VANETs. The proposed model also highlights the significance of intelligent adaptive techniques in obtaining enhanced network performance.

Abstract Advert placement in sports broadcasts is a growing strategy to boost sponsor visibility without disrupting live gameplay. Achieving realism, however, requires careful handling of scene geometry and dynamic occlusions from players and the sports ball. In this work, we propose an occlusion-aware and perspective-consistent framework specifically for virtual advert placement in the soccer penalty area. We introduce an automatic procedure to select a geometrically consistent quadrilateral region inside the penalty area from predicted field coordinates, which is then used for homography-based warping. We integrate instance-level occlusion masks with Laplacian Alpha Blending for dynamic occlusion-aware blending so that the virtual advert is correctly placed behind players and the ball. Quantitative evaluations demonstrate that our occlusion-aware advert placement method preserves high visual fidelity with an average SSIM of 0.97 and PSNR of 31.6 dB, while maintaining temporal consistency with flicker index increase of <7%. Furthermore, we analyze occlusion preservation by comparing advert insertion with and without occlusion handling. A decrease in this metric indicates that objects overlapping the advert region become incorrectly hidden after advert insertion. The results highlight the importance of occlusion-aware blending for maintaining scene integrity and visual realism. By effectively managing occlusions, the proposed framework reduces visual artifacts and improves perceptual quality, producing augmented sports footage that is realistic and visually coherent.

Effective congestion control algorithms (CCAs) are crucial for the smooth operation of Internet communication infrastructure. CCAs adjust transmission rates based on congestion signals, optimizing resource utilization and user experience. However, existing studies, both rule-based and learning-based CCAs, often struggle with generalization and underperform when deployed in real-world environments. When applied to unseen network conditions, hand-crafted schemes or pre-trained models may experience significant performance degradation. To address this challenge, we propose MetaCon, a novel adaptive Internet congestion control approach based on meta-reinforcement learning. MetaCon leverages knowledge learned from prior scenarios to quickly adapt to new environments. Experimental results show that MetaCon outperforms existing algorithms by exhibiting superior generalization and achieving better transmission performance across a wide variety of network conditions.

The rapid growth of Intelligent Transportation Systems (ITS) has necessitated the development of resilient Vehicular Ad Hoc Networks (VANETs) to provide uninterrupted Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication. VANETs have considerable obstacles, such as frequent disconnections, restricted coverage, and elevated latency resulting from the sparse deployment of Roadside Units (RSUs). This paper presents a UAV-assisted VANET system that utilizes dynamic UAV deployment and Q-learning-based congestion-aware routing to mitigate these constraints. The UAVs act as intelligent mobile relays, optimizing coverage, enhancing data dissemination, and minimizing communication disruptions. This method employs Particle Swarm Optimization (PSO) for adaptive UAV positioning and Machine Learning (ML) for efficient packet routing. This guarantees continuous connectivity, reduces latency, and improves network resilience in a dynamic vehicular environment. Simulation findings illustrate the system’s scalability and efficacy, enhancing the Packet Delivery Ratio (PDR) from 65% to over 90% in high-density environments, while concurrently decreasing the average hop count by more than 50% and the end-to-end latency by up to 66%. The suggested method facilitates scalable and adaptable UAV-assisted VANET systems, markedly enhancing the reliability and efficiency of next-generation ITS.

Efficient spectrum resource allocation is essential for vehicular networks to ensure seamless connectivity in dynamic environments. However, conventional mathematical and deep reinforcement learning (DRL) methods suffer from scalability challenges and privacy concerns due to centralized training requirements. In addition, the high mobility of vehicles leads to frequent topology changes and switching, making static spectrum allocation schemes ineffective. To address these challenges, this paper investigates a joint federated learning (FL) and proximal policy optimization (PPO) framework (FL-PPO) for spectrum resource allocation in vehicular networks. In our proposed framework, each vehicle independently trains a local DRL model using PPO. At the same time, the base station implements a federated average (FedAvg) algorithm to aggregate models, thereby enhancing global learning while preserving data privacy. By combining FL with DRL, the proposed method improves scalability, adaptability, and safety in highly dynamic vehicular environments. Simulation results demonstrate that FL-PPO outperforms centralized DRL and heuristic baselines, achieving higher spectrum capability and better packet delivery, making it a promising resource allocation solution for vehicular networks.

Information-Centric Networking (ICN) is a promising future network architecture that shifts the host-based network paradigm to a content-oriented one. Over the past decade, numerous ICN congestion control (CC) schemes have been proposed, tailored to address congestion issues based on ICN’s transmission characteristics. However, several key challenges still need to be addressed. One critical issue is that most existing CC studies for ICN do not consider the diverse Quality of Service (QoS) requirements of modern network applications. This limitation hinders their applicability across various applications with different network performance preferences. Another ongoing challenge lies in improving transmission performance, particularly considering how to appropriately coordinate congestion control participants to enhance content retrieval efficiency and ensure reasonable resource allocation, especially in multipath scenarios. To tackle these challenges, we propose QSCCP, a QoS-aware congestion control protocol built upon NDN (Named Data Networking), a well-known ICN architecture. In QSCCP, diverse QoS preferences of various traffic are supported within a collaborative congestion control framework. A novel multi-level, class-based scheduling and forwarding mechanism is designed to ensure varied and fine-grained QoS guarantees. A distributed congestion notification and precise feedback mechanism is also provided, which efficiently collaborates with an adaptive multipath forwarding strategy and consumer rate adjustment to rationally allocate network resources and improve transmission efficiency, particularly in multipath scenarios. Extensive experimental results demonstrate that QSCCP satisfies diverse QoS requirements while achieving outstanding transmission performance. It outperforms existing schemes in throughput, fairness, delay, and packet loss, with a rapid convergence rate and excellent stability.

Abstract Unmanned aerial vehicle (UAV)-based data gathering from wireless sensor networks is one of the recent research topics that has currently attracted research interest. One of the challenges for the UAV-aided WSN data collection efforts is to design an energy-efficient UAV/drone communication with arbitrarily dispersed ground sensors by improving the ground network structure. This paper aims to develop a technique titled UAV Fuzzy Travel Path' that supports UAV smooth path design and enables ground network topology shifting. A comprehensive UAV-based data collection model is proposed to enable dynamic orchestration/re-orchestration of wireless ground sensors to jointly improve network performance and UAV path fluidity. This provides a more flexible ground network framework that can be restructured based on network demands and UAV optimal paths, effectively allowing for a software-defined network concept. The main contribution of this work is the implementation of the software-defined wireless sensor network on the ground network that adaptably supports the movement of the UAV and enhances the communication network’s energy efficiency with a proposed latency analytical analysis via network orchestration/re-orchestration phases. The main significance of this research is in offering a flexible span for UAV path design than being fixed in one strict route for data gathering purposes. Four various simulation tools are employed for modelling and performance evaluation, namely MATLAB, CupCarbon, Contiki-Cooja and Mission Planner. The proposed software-defined ground network system demonstrates encouraging results in terms of network performance metrics including energy consumption of UAV versus ground sensor nodes energy usage, packet delivery rate, and the communication time of the ground orchestrated or/and re-orchestrated network.

In the rapidly evolving landscape of federated learning (FL), hierarchical architectures are pivotal for improving computational efficiency and safeguarding data privacy. A key challenge in this research area is the optimal selection of edge servers, crucial for executing distributed learning tasks across multiple clients and servers efficiently. Traditional selection methods falter due to their inability to dynamically handle the uncertainties in network conditions and server capabilities. To addressing this weakness, we propose a fuzzy logic-based approach that optimizes edge server selection in a novel smart way, thus enhancing resource allocation by efficiently handling the unpredictable nature of network environments and servers performance. This method is integrated with a previously developed scheme for selecting an optimal subset of clients, thereby establishing a comprehensive framework that significantly boosts the performance and reliability of FL networks. The performance of our approach is validated through real-world experiments and the results demonstrate its superiority over existing methods in terms of accuracy and processing time.

Implicit neural representations have recently demonstrated considerable potential in various applications, including video compression and reconstruction, owing to their rapid decoding speed and high adaptability. Based on the most advanced neural representation for Videos (NeRV), Expedite Neural Representation for Videos (E-NeRV) and Hybrid Neural Representation for Videos (H-NeRV) primarily boost performance by enhancing and broadening the NeRV network’s embedded input, whereas the NeRV module—the central component involved in video reconstruction—has attracted less attention. With a focus on high-frequency data in the frequency domain, this paper proposes a High-frequency Spectrum Hybrid Network (HFS-HNeRV), which adopts effective high-frequency data from the frequency domain to generate image details. Its core, HFS-HNeRV block, is a novel NeRV module, which adds the high-frequency spectrum convolution module (HFSCM) to the original one. This module extracts and emphasizes high-frequency features through the frequency domain attention mechanism, which not only provides superior performance, but also enhances the local detail recovery in video images. As an upgrade of the NeRV module, it has exceptional performance in terms of adaptability and versatility. It can conveniently substitute in a variety of current NeRV designs without requiring significant alterations to attain enhanced performance. Furthermore, this paper also introduces the High-frequency Spectrum (HFS) loss function to further mitigate the blurriness issue caused by the loss of high-frequency information during image generation. In the video compression task, the proposed HFS-HNeRV network outperformed NeRV, E-NeRV and HNeRV with an improvement of +5.68 dB, +4.46 dB, and +0.98 dB in reconstruction quality (PSNR), respectively.

Nowadays, there is high commercial demand for product replacement which places the products virtually in Key Opinion Leader’s (KOL’s) social media videos. However, one of the challenges of placing the products virtually is the KOL segmentation. Since KOLs often hold products in front of them, it requires the segmentation to segment not only humans but also different products. This paper introduces the state-of-the-art deep learning method, namely RSUDISNet, for KOL segmentation. The proposed technique integrates two deep Convolutional Neural Network (CNN) technologies. One is the Matting Objective Decomposition Network (MODNet), which segments KOLs well but not the products blocking the KOLs. The other one is the two-level nested U-structure network (U2Net) based on the salient object detection method to segment the objects well, but not the KOL. The key technique of the proposed research is to employ the feature of the U2Net to embed the MODNet to overcome the problem of KOL segmentation. Since both MODNet and U2Net are lightweights, the combined network can be used for real-time scenarios. After that, the Intermediate Supervision (IS) training strategy is utilized to overcome the overfitting. The experimental results show that our proposed method outperforms the MODNet and U2Net.

Senior individuals are among the most frequent users of healthcare services, accounting for approximately 12% of the public sector, primary, and hospital care. Most elderly people who live alone and are not monitored are at risk of losing their lives because of a sudden fall caused by a slip, trip, or health issue and are not reported to an emergency department in time to receive immediate treatment. Thus, reliable and cost-effective e-health technologies are essential for solitary older adults. This research aims to predict potential falls in elderly individuals by detecting anomalies through continuous monitoring. The proposed prediction technique with the Fall Prediction Algorithm learns and performs tasks using Fuzzy rules. The acquired results are categorized based on the prediction risk levels. The proposed fall risk prediction model is evaluated using data collected from three different sources and the findings are compared to the Morse Falls Scale. According to the results obtained, the suggested prediction model has a total accuracy of 95.24%, sensitivity of 93.75%, and specificity of 100%. With these advancements in the proposed heterogeneous technology, elderly falls can be predicted earlier to save their lives.

An accurate heart rate (HR) estimation using a radar sensor is challenging in real-life situations due to frequent changes in a person’s sitting position and posture. Furthermore, radar signal is affected by the presence of clutter noise, the harmonics associated with respiration (RR), and the movements of the body. To address these challenges, this article proposes a real-time beam steering algorithm and a signal processing technique based on Resonance Sparse Spectrum Decomposition (RSSD). Our beam steering method dynamically calculates the range–angle values of the target during the scanning phase and determines the target’s position at the beginning of each measurement cycle. This allows the beam-steered signal to be directed toward the individual, thereby improving the signal-to-noise ratio (SNR). We present a novel signal processing method based on RSSD that leverages sub-band energy distribution to optimize the quality factor (Q) and the subsequent extraction of HR using harmonics. The Q factor defines the resonance property of an oscillatory signal, and hence, signal components with similar center frequency bands but with a different quality factor, Q, can be separated and sparsely represented. The RSSD-based algorithm mitigates the effects of clutter and random body motion from the phase signal, which significantly enhances HR estimation accuracy. Comprehensive experiments performed under various realistic conditions demonstrate that the HR accuracy remains consistently high at 98.72% within a 4 m range across all azimuth angles.

This research proposes a dynamic resource allocation method for vehicle-to-everything (V2X) communications in the sixth generation (6G) cellular networks. Cellular V2X (C-V2X) communications empower advanced applications but at the same time bring unprecedented challenges in how to fully utilize the limited physical-layer resources, given the fact that most of the applications require both ultra low latency, high-data rate and high reliability. Resource allocation plays a pivotal role to satisfy such requirements as well as guarantee Quality of Service (QoS). Based on this observation, a novel fuzzy-logic-assisted$Q$learning (FAQ) model is proposed to intelligently and dynamically allocate resources by taking advantage of the centralized allocation mode. The proposed FAQ model reuses the resources to maximize the network throughput while minimizing the interference caused by concurrent transmissions. The fuzzy-logic module expedites the learning and improves the performance of the$Q$-learning. A mathematical model is developed to analyze the network throughput considering the interference. To evaluate the performance, a system model for V2X communications is built for urban areas, where various V2X services are deployed in the network. Simulation results show that the proposed FAQ algorithm can significantly outperform deep reinforcement learning,$Q$-learning and other advanced allocation strategies regarding the convergence speed and the network throughput.

The noncontact measurement and monitoring of human vital signs has evolved into a valuable tool for efficient health management. Because of the greater penetration capability through material and clothes, which is less affected by environmental conditions such as illumination, temperature, and humidity, mmWave radar has been extensively researched for human vital sign measurement in the past years. However, interference due to unwanted clutter, random body movement, and respiration harmonics make accurate retrieval of the heart rate (HR) difficult. This article proposes a resonance sparse spectrum decomposition (RSSD) algorithm and harmonics used algorithm (HUA) for accurate HR extraction. RSSD addresses the clutter and random body movement effects from phase signals, while HUA uses harmonics to extract HR accurately. A set of controlled experiments was conducted under different scenarios, and the proposed method is validated against ground truth HR/RR data collected by a smart vest. Our results show an accuracy of up to 98%–100% for distances up to 2 m. The method substantially improves HR estimation accuracy by effectively mitigating the effects of noise in the phase signal, even under heavy clutter and moderate body movement. Our results demonstrate that the proposed method effectively counters harmonic interference for accurate estimation of HR comparable to RR estimation up to a distance of 4 m from the radar sensor.

With unprecedented advances in cutting-edge technologies such as Internet of Things (IoT), network virtualization, digital twin, etc., various applications such as vehicular networks (VN) need to be modelled and evaluated using suitable tools. Given the dynamic nature of VN, there is a need for a virtual flexible model that can be tested prior to implementation to avoid real-time network disruptions. It also offers network maintenance without requiring major modifications to the model in real-life execution. Therefore, software-defined networking (SDN) is one of the approaches that can provide flexibility to such applications as well as other applications such as clustering for trap monitoring using UAV. Applying this advanced technology to vehicular networks can involve significant costs and complex tools. Therefore, utilizing tools such as the Contiki-Cooja network simulator allows for trailing network scenarios and testing performance virtually to obtain the best network topology that can be applied to the physical network. The aim of the paper is to offer the modelling and implementation tools that can be employed towards concept development and testing. It provides insight into the ability of various accessible tools, including software and hardware, to investigate the concept of flexible vehicular network grouping and network re-orchestration.

Information-Centric Networking (ICN) has been proposed to provide a scalable and efficient content delivery solution. To support different kinds of applications in ICN, a practical congestion control mechanism should consider various traffic and the corresponding requirements of the quality of service (QoS), which is ignored by most of the existing schemes. In this paper, we propose a differentiated service-based congestion control protocol (DSCCP) for ICN. DSCCP defines the service classes of various ICN traffic and performs the class-based hop-by-hop Interest shaping at intermediate nodes. Meanwhile, it employs an explicit rate feedback mechanism to notify consumers about available network resources. It also provides feedback for the forwarding strategy of the router to adjust the forwarding probability of each interface. Additionally, a punishment tactic is used to tackle misbehaving consumers by limiting the Interest forwarding rate. The simulation results show that DSCCP can ensure the class-based bandwidth allocation among consumers with different service classes, as well as, quickly converge to a high throughput with low latency and low packet loss rate.

Each blockchain’s node needs to store a backup of all blocks, resulting in the whole network needs O(n) storage space, which greatly affects the nodes’ scalability. Parallel proof of vote(PPoV) is a permissioned blockchain algorithm that uses block groups as the basic data structures. This paper proposes a data lightweight scheme for PPoV. In the bock group generation stage, the BLS algorithm is used to realize signature aggregation, and the storage space of block signature and vote signature is reduced from O(n) to O(1) without affecting the performance. In the storage stage, we use erasure code to implement storage partition for block groups and ensure the real-time recoverability of complete data. To speed up reading, the timeline-based model applies different storage strategies for hot and cold data. The experimental results show that the empty block group generated by BLS aggregation signature is smaller and less sensitive to the number of nodes. And the reduction ratio of storage space under a large number of transactions can be similar to the number of normal nodes.

In this paper, we spotlight vehicle-to-everything (V2X) communications in 5G cellular networks. Cellular V2X (C-V2X) communications in 5G enable more advanced services with requirements of ultra-low latency and ultra-high reliability. How to make full use of the limited physical-layer resources is a key determinant to guarantee the quality of service (QoS). Therefore, resource allocation plays an essential role in exchanging information between vehicles, infrastructure, and other devices. In order to intelligently and reasonably allocate resources, a self-adaptive fuzzy logic-based strategy is developed in this paper. To evaluate the network performance for this adaptive strategy, a system model for V2X communications is built for urban areas, and typical safety and non-safety services are deployed in the network. Simulation results reveal that the proposed fuzzy logic-based algorithm can substantially improve resource utilization and satisfy the requirements of V2X services, compared with prior counterparts, which cannot provide guaranteed services due to low resource utilization.

Basic Safety Messaging plays a crucial role to provide road safety in vehicular ad-hoc networks (VANETs). To avoid potential accidents, vehicles periodically broadcast safety information to neighboring vehicles. However, due to transmission collisions, fading channels and other factors, vehicular networks usually suffer a low packet delivery ratio (PDR) and a large delay, which are intolerant of many safety applications. To tackle these issues, this paper proposes a hybrid medium access control (MAC) protocol for basic safety message (BSM) dissemination based on the framework of Dedicated Short-Range Communication (DSRC). Its partially centralized and partially distributed characteristic not only can effectively suppress the collisions, but keep compatibility with IEEE 802.11p. In addition, the integration of Physical-Layer Network Coding (PNC) and Random Linear Network Coding (RLNC) further strengthens the reliability and efficiency for BSM dissemination. Both the theoretical analysis and comprehensive simulations indicate that, compared with existing schemes, the proposed protocol can significantly improve the PDR by a range of 20% to 300%. Meanwhile, in terms of normalized throughput, it increases by varying percent between 20% and 160% in different scenarios.

Data dissemination is a fundamental, yet one of the pressing issues in vehicular communication due to the associated high dynamicity. The vehicular network topology frequently keeps changing, limiting the lifetime of the links. This imposes serious difficulties in data transmission, especially in multi-hop applications as the vulnerability escalates when the packets are transmitted over multiple hops. The broadcasting based Vehicular Ad-hoc Network (VANET) routing protocols struggle to cope with this dilemma due to the lack of global network information. But, with novel Software Defined Vehicular Network (SDVN), link stability can be better scrutinized pertaining to the availability of global network view . Yet, the architectural challenges in SDVN can limit the availability of network information confining the empowerment of Software Defined Networking (SDN). Thus, in this paper, we introduce a link connectivity aware novel routing framework for a general SDVN acknowledging the limitations in data availability as well. The routing protocol comprises of both centralized and distributed routing techniques and makes use of unicast , broadcast, and store, carry and forward concepts. The resulting tribrid routing framework focuses on finding stable enough shortest routes that can deliver a given set of packets satisfying the required Quality of Services (QoSs) in terms of latency. In case of network uncertainties, the protocol incorporates broadcasting based distributed techniques along with unicast routing . In sparse network conditions, the model aims to deliver the packets in the optimal path with the least store and carry time within the QoS requirement. The routing protocol follows an incremental algorithm where extracted paths are tested for the feasibility on a case by case basis.

Real-time traffic updates, safety and comfort driving, infotainment, and so on, are some envisioned applications in vehicular networks. Unlike traditional broadcast, network-coding-assisted broadcast can satisfy multiple vehicles with different data items in a coded form. However, server side encoding requires the prior knowledge about vehicles’ cache information for the successful decoding at the vehicles’ sides. The explicit cache upload from vehicles to Road Side Unit (RSU) wastes upload bandwidth. In multi-RSU vehicular networks, we propose a Cooperative Cache Transfer-based On-demand Network Coded Broadcast called CCTCB. In the proposed CCTCB approach, vehicles do not need to upload their cache information to the server, rather the RSU server learns the vehicles’ cache intrinsically. We derive a probabilistic model to analyze the coding opportunity in the proposed cooperative cache transfer mechanism incorporating vehicle mobility. The comprehensive simulation results validate the superiority of the proposed approach.

How to achieve reliable routing has always been a major issue in the design of communication networks, among which mobile ad hoc networks (MANETs) possess the most adversarial networking environment due to the absence of fixed infrastructure, the nature of open transmission media and the dynamic network topology. These characteristics also make the design of routing protocols in MANETs become even more challenging. In this paper, we propose an evolutionary self-cooperative trust (ESCT) scheme that imitates human cognitive process and relies on trust-level information to prevent various routing disruption attacks. In this scheme, mobile nodes will exchange trust information and analyze received trust information based on their own cognitive judgment. Eventually, each node dynamically evolves its cognition to exclude malicious entities. The most attractive feature of ESCT is that they cannot compromise the system even if the internal attackers know how the security mechanism works. In this paper, we evaluate the performance of ESCT scheme under various routing disruption attack situations. Simulation results affirm that ESCT scheme promotes network scalability and ensures the routing effectiveness in the presence of routing disruption attackers in MANETs.

Unmanned aerial vehicles (UAVs) have attracted a lot of attention due to their enormous potentiality in civil and military applications over the past years. In order to allow accurate control action of UAV, a robust and real-time state estimation technique is required. In this paper, we propose a Kalman filter based UAV state estimation technique when the communication takes place over wireless links in an Internet of Things (IoT) network. We consider that a set of sensors observes the state of the UAV and transmits the observation to a control center (central server) over a distributed wireless IoT network. To deal with the communication impairments due to wireless communication links between the UAV's sensors and the IoT system components, e.g., IoT gateways, a Bose-Chaudhuri-Hocquenghem coded communication system is presented. Based on the received signals at the IoT gateways, a global state estimation technique is proposed. Performance of the proposed communication and estimation scheme is demonstrated through numerical results for different conditions. From the comparison with a conventional estimation scheme, it is observed that the proposed scheme significantly outperforms the conventional scheme in terms of state estimation and error performance.

Recently, much attentions have been paid to network coding-assisted data broadcast in vehicular networks. However, majority of the works consider all the accessed data items are the same size. In this work, we have studied the network coding-assisted heterogeneous on-demand data access in vehicular networks. Firstly, we have investigated the less efficiency of conventional coding assisted approach in accessing heterogeneous data items in real-time vehicular environment. Due to ignoring the impact of heterogeneous data items in decoding, the conventional coding does not achieve expected performance in accessing data items with diverse size. Secondly, based on our observations, we have proposed a new algorithm. The proposed network coding assisted approach exploits the different MCSs (Modulation and coding schemes) of IEEE 802.11p physical layer for leveraging the variable serving rate considering the dynamic positions' of vehicles along with the vehicle mobility. Thirdly, we have built a vehicular simulation environment and evaluated the performance of the proposed approach along with competitive no-coding and coding-assisted approaches under various circumstances. The results show that the proposed approach outperforms the state-of-the-art approaches in terms of improving the on-demand requests serving capability and reducing the data access time.

The dynamic nature of vehicular networks imposes a lot of challenges in multi-hop data transmission as links are vulnerable in their existence. Thus, the packets frequently find it difficult to get through to the destination as links only exist for a limited amount of time. The broadcasting based conventional routing protocols struggle to cope with these situations due to the lack of global network information. But, with the novel Software Defined Vehicular Network (SDVN) architecture, link stability can be better scrutinized pertaining to the availability of global network view. However, due to the imperfections in the SDVN architectures and dynamicity in vehicular networks, the control plane may not possess all the network information at a given point in time. Considering all these factors, in this paper, we introduce a novel routing framework for SDVN which is composed of both centralized and distributed routing mechanisms. The resulting hybrid routing framework focuses on finding stable multiple short routes that can deliver a given number of packets, and in case of uncertain network conditions, a broadcasting approach is adopted. The overall problem is formulated as a minimum cost capacitated flow problem and the effectiveness is demonstrated comparatively via extensive simulations.

Recently, a new paradigm has emerged, named as Software Defined Vehicular Network (SDVN) which applies the concept of Software Defined Networking (SDN) in Vehicular Ad-hoc Network (VANET), to overcome the shortcomings in vehicular networks. With the introduction of SDN, VANET has been provided with flexibility and programmability along with a performance improvement . However, the improvement comes at a cost of higher operational delay because, the controllers are placed far away from the data plane in the existing SDVN architectures . As an alternative, we have previously proposed to bring the control plane down to Road Side Unit (RSU). In this study, we further extend this work and introduce a hierarchical distributed controller architecture where the top tier of controllers are regionally distributed on the Internet and the bottom tier of controllers are placed in several selected RSUs closer to the vehicles so that the latency induced by the system becomes low. We further present a novel controller placement model for the RSU level controllers based on the p-median facility location problem with the delay and the significance of the RSU location as the factors to achieve the optimization heuristically as an integer quadratic programming problem . With the help of the simulation results, we show that our proposed controller placement model can optimize the placements of controllers with a lower latency compared to other possible controller placement methods including the existing SDVN architectures and conventional VANETs.

Through the embedded processors and communication technologies, vehicles are increasingly being connected with the Internet of Things. Recently, much attentions have been paid to network-coding-assisted data broadcast in vehicular networks. However, majority of the works consider all the accessed data items are the same size. In this paper, we have studied the network coding-assisted heterogeneous on-demand real-time data access in vehicular networks. First, we have investigated the less efficiency of conventional coding assisted approach in accessing heterogeneous data items in real-time vehicular environment. Due to ignoring the impact of heterogeneous data items in decoding, the conventional coding does not achieve expected performance in accessing data items with diverse size. Second, based on our observations, for efficiently serving heterogeneous data items, we have proposed a dynamic threshold-based coding-assisted real-time data broadcast approach called earliest deadline firstΘ. Third, we have derived the probabilistic analysis of the system performance of the proposed approach and the state-of-the-art approaches. Fourth, based on our further investigations, we have proposed another approach, called inverse of slack time multiply distance with THRESHOLD (Θ) (ISXDΘ). The proposed network coding-assisted ISXDΘexploits the different modulation and coding scheme of IEEE 802.11p physical layer for leveraging the variable serving rate considering the dynamic positions of vehicles along with the vehicle mobility. The comprehensive simulation results demonstrate the efficacy of the proposed approaches over the state-of-the-art approaches in terms of improving the on-demand requests serving capability and reducing the system response time.

Data transmission in vehicular networks suffers heavily from its inherent dynamic nature as the connections between vehicles exist only for a limited amount of time. Therefore, the packets frequently find it hard to get through to the destination in multi hop data transmission as links are vulnerable in their existence. Conventional Vehicular Ad-hoc Network (VANET) routing protocols struggle in this sense, as they do not have a global network view to tackle these scenarios. But Software Defined Networking (SDN) fills this gap in VANET, and the packets can be routed better by coping with the dynamic nature of the network more effectively. However, existing routing schemes in Software Defined Vehicular Networks (SDVN) have utilized this advantage only in finding the shortest path. As an alternative, we introduce a novel packet routing framework which scrutinizes the dynamic nature of wireless links. Rather than just focusing on the shortest path, we also bring the focus to the stability of the route in finding the optimal paths. Thus, we formulate the packet routing problem as a minimum cost capacitated flow problem and find multiple paths which are stable enough to deliver a given number of packets successfully.

Road Side Units (RSUs)-based data communication (V2I) is an increasingly popular technique in vehicular networks to alleviate the frequent vehicle-to-vehicle (V2V) communication problem. On-demand broadcasting is a scalable approach for supporting large clients with dynamic demands. However, the performance of the traditional on-demand broadcast can be improved significantly with the incorporation of network coding in server side broadcast. Although majority of the coding based studies assume the sizes of the server's accessed data items are the same, in reality, the sizes of the accessing data items are different. Keeping in mind of two important characteristics, from both the the vehicles' submitted requests point of view and the server's serving time point of view, we propose an efficient dynamic threshold based coding based data broadcast approach. The proposed approach considers both the deadline of request and the heterogeneity of accessed data item in scheduling, which can minimize the number of deadline missed requests and reduce the overall data access time. Simulation results verify the efficiency of our proposed approach over the traditional approaches.

Cooperative forwarding has shown a substantial network performance improvement compared to traditional routing in multi-hop wireless networks. To further enhance the system throughput, especially in the presence of highly congested multiple cross traffic flows, a promising way is to incorporate the multi-radio multi-channel (MRMC) capability into cooperative forwarding. However, it has been said that incorporating MRMC into cooperative forwarding can be considered as a trade-off between multiplexing and spatial diversity and what choice the neighbouring nodes should make is non-trivial. In this paper, we propose a new cooperative forwarding mechanism for multi-radio multi-channel multi-flow wireless networks. The performance is studied in highly congested network and under the situation where the same set of forwarding candidates is being used for multiple flows. Performance evaluation shows that the integrated mechanism achieves about 200% of throughput improvement compared to the single-radio single-channel case.

In vehicular ad hoc networks, the basic safety message (BSM) is periodically broadcast by every vehicle on the road. By exchanging BSMs with neighbors, vehicles aggregate the collected information to get aware of driving environment and react promptly in case of any danger. The BSM dissemination is particularly crucial for vehicles at urban road intersections to avoid car collisions. However, blocking from buildings and obstacles at road corners creates a non-line-of-sight (NLOS) condition for vehicle-to-vehicle communications. The direct broadcasting cannot guarantee a reliable BSM delivery. To solve this problem, we consider the relay-assisted scheme and apply the repetitive transmission pattern to increase the successful reception probability. By exploiting the benefit of network coding, we propose two promising network coded relaying schemes, coding at one relay node (RT-NCI) and coding at all relay nodes (RT-NC), to enhance the reliability of BSM dissemination and improve the system scalability. The superiorities of the proposed schemes are verified by simulation results.

Fog-based radio access networks (F-RAN) are poised to play a significant role in future 5thgeneration (5G) cellular networks by harnessing the distributed resources of collaborative edge devices to deliver localized RAN services to the end-users. Through ingestion and processing of end-user tasks close to their sources, F-RAN has potential to meet the stringent latency and bandwidth requirements of 5G services and applications. Due to the multitude of edge devices with different resource capacities that can be selected by the fog access point (FAP) as service nodes to process an end-user task, an important issue is deciding which service node(s) should be assigned to process what tasks from endusers in the F-RAN. The tasks here refer to user processing tasks that would have normally performed by the FAP or remotely by the cloud. In this paper, we introduce the concept of virtual FAPs (v-FAPs) formed by a number of local devices such as WiFi access points, femtocell basestations and the more resource-rich end-user devices under the coverage and management of the FAP. This paper focuses on addressing the task assignment problem by proposing a service load balancing algorithm for the v-FAPs. We model the user tasks as a task graph and the service nodes as an edgeless service graph. We then formulate an optimization problem to find the optimal assignment of tasks with the objective of balancing loads at the service nodes.

In radiometric fingerprinting, a transmitter is identified from its unique electromagnetic emission. A unique radiometric fingerprint can be used to establish the identity of a specific wireless device in order to prevent masquerading/impersonation attacks. Recent research in radiometric fingerprinting have introduced promising new features and techniques to demonstrate its feasibility for security and privacy applications in wireless devices. However less attention is given to the robustness of radiometric fingerprint against impersonation attacks. In our previous work, we have evaluated the impersonation attack on radiometric fingerprinting using low-cost transceivers. In our previous work, the impersonator was unaware of its own transceiver impairments, which leads to lower success rate. In this research work we are considering a sophisticated impersonator aware of its transceiver response and producing an impairment free legitimate radio signal of the target device. Our analysis shows that successful impersonation is largely dependent on the quality of the legitimate receiver.

Basic Safety Messaging (BSM) is a crucial application to provide road safety in vehicular ad-hoc networks (VANET). This paper proposes an efficient and reliable MAC protocol for BSM packets dissemination based on the framework of Dedicated Short-Range Communication (DSRC). It perfectly integrates Physical-Layer Network Coding (PNC) and Random Linear Network Coding (RLNC) in both roadside unit (RSU) and onboard unit (OBU) nodes. Comprehensive simulation shows that compared with the existing schemes for BSM dissemination, the proposed protocol achieves both high flexibility and excellent performance in packet delivery ratio (PDR).

Software Defined Vehicular Networks (SDVN) brings a set of attractive features to vehicular networks along with an upgrade in the performance. Yet, SDVN suffers from frequently compelling to contact the centralized control plane, which in turn generates a high latency and packet overhead in the communication. The current solution to reduce the delay, proactive approach, does not bring the packet overhead down and impose a lot of stress on the controller with a decline of Packet Delivery Ratio (PDR). As an alternative, we introduce a source routing based flow instantiation operation with intelligent route caching that reduces the extent of communication with the control plane, but still manages to utilize the knowledge of controller while maintaining a lower latency and packet overhead.

In this paper, we develop a comprehensive analytical framework to characterize the performance of device-centric content availability in device-to-device (D2D) networks. Modeling the locations of devices as a variant of Thomas cluster process, we derive the coverage probability of a typical device when its content of interest is available at its kth closest device within the same cluster. Using the coverage probability results, we characterize the area spectral efficiency (ASE) of the whole network. A key intermediate step in this analysis is the derivation of the distributions of distances from the typical device to both the intra- and inter-cluster devices. Our analysis reveals that an optimum number of D2D transmitters must be simultaneously activated per cluster in order to maximize ASE. This can be interpreted as the classical tradeoff between more aggressive frequency reuse and higher interference power. Our analysis also quantifies the best and worst case performance of the clustered D2D networks both in terms of coverage and ASE.

Data delivery in opportunistic networks requires robustness and resiliency due to the mobility and the probabilistic propagation of the channels caused by fading. The store-carry-forward (SCF) based routing has become a conventional data forwarding mechanism in such networks. Due to the information dissemination nature of SCF routing, information epidemics control has become a necessary mechanism in SCF routing to prevent from the epidemics outbreak. In this paper, we propose an information epidemics control approach which provides earlier control signal distribution time and faster recovery rate for the data delivery solutions in opportunistic networks. We study the effectiveness of the proposed scheme based on the susceptible-infected-recovered (SIR) model and prove that it provides a higher vaccination rate and recovery rate. Due to the flexibility of the proposed scheme, it can be integrated with any SCF-based routing. We integrate the proposed vaccinating mechanism in a SCF-based routing and show that a robust data delivery is achieved and a substantial amount of unnecessary transmissions are well deterred.

Network coding has been introduced as a new paradigm for network routing protocols in recent years. The wide range of advantages of network coding, such as energy saving, throughput improvement and congestion mitigation, have been demonstrated in many practical systems. However, the nature of packet mixing, optimization of forwarding nodes selection cause the network coding based routing protocols vulnerable to routing attacks. In this paper, we conduct a detailed analysis of various security threats that attack on different components of intra-flow network coding based routing schemes, and provide an extensive simulation study of their impacts on the network performance. An adequate understanding of both threats and vulnerabilities of current network coding systems are essential to effectively design of defense mechanism. This paper is served as a preliminary guide in the effort of achieving security for network coding based wireless routing.

To maintain tractability, interference field is often modeled as a homogeneous Poisson Point Process (PPP) in the analysis of wireless networks. While it provides meaningful first-order results, it falls short in modeling the effect of interference management techniques, which typically introduce some form of spatial interaction among transmitters. In some applications, such as cognitive radio and device-to-device networks, this interaction results in the formation of holes in an otherwise homogeneous interference field. The resulting interference field can be accurately modeled as a Poisson Hole Process (PHP). Despite the importance of PHP in modeling wireless networks, exact characterization of the interference experienced by a typical node in a PHP is an open problem. In this paper, we introduce a new approach to modeling the PHP, in which we dissolve the holes in such a way that it results in an equivalent non-homogeneous PPP, which is much more amenable to shot-noise analysis. Using this approach, we derive new lower and upper bounds on the Laplace transform of interference in a PHP. The new bounds are compared numerically to the known approaches and are shown to be very tight under various operational regimes.

Road Side Units (RSUs) installed alongside the road in Vehicular Ad Hoc Networks (VANETs) act as buffer points and alleviate the frequent vehicle-to-vehicle connectivity problem. In VANETs, submitting multi-item query is a common phenomenon, for instance, a query with required traffic information of multiple routes. Unlike the single item query, a multi-item query only be satisfied successfully if all the required data items are served within the stipulated deadline. In serving multi-item query, the system also needs to address the query starvation problem which causes due to the presence of less popular data items in the same query with the high popular data items. In this paper, for serving multi-item queries efficiently, we have proposed an approach which integrates network coding with on-demand broadcasting in multi-RSU VANETs. The traditional on-demand broadcast only disseminates a single data item in a broadcast tick which restricts the maximum channel bandwidth utilization. On the contrary, our proposed approach uses network coding through which multiple data items can be broadcast in a single broadcast. Again, our proposed network coding based approach learns the cache information of vehicles intrinsically which cuts the overhead of network coding, namely avoids uploading cache information of vehicles to the RSU server explicitly. In addition, the proposed approach is equally good to integrate both with the item-level and query-level on-demand scheduling algorithms for maximizing the system performance. Finally, we have performed an extensive simulation experiment to demonstrate the superiority of our proposed approach against the traditional broadcasting system for a number of on-demand scheduling algorithms.

The usage of Road Side Units (RSUs) acting as a buffer point in VANETs alleviates the intermittent vehicle-to-vehicle (V2V) connectivity problem. However, due to the vehicle mobility and the short RSU-transmission-range, a vehicle dwells short time inside an RSU. Nevertheless, quick response from the RSU server, helps a driver to make a quick decision while driving. Network coding is known to be efficient for broadcasting multiple data items in a single packet by encoding requested data items based on the cache information of the vehicles. This can significantly improve the broadcast bandwidth usage as well as reduce the response time of the system. However, this requires the prior knowledge of cached data items of vehicles. Hence vehicles need to upload the cache information to the RSU server. This wastes upload bandwidth. In multi-RSU VANETs, we propose an approach to apply network coding in such a way so that vehicles do not need to upload their cache information to the server. Applying network coding improves the broadcast performance of an RSU in terms of minimizing the deadline miss ratio of the generated requests by vehicles, and reducing the response time of serving requests by the RSU server. Simulation results support our claims.

Basic safety message(BSM) or heartbeat message is periodically broadcast by each vehicle on the road, conveying vehicle's instantaneous position and driving state. The vehicular communication network enables the fast exchange of BSMs with neighboring vehicles which assists drivers in acquiring the local driving environment and maneuvering promptly in case of any potential hazard. Such message is exceptionally crucial for vehicles at road intersection to avoid collisions. In this paper, we propose a novel BSM broadcast scheme using random linear network coding (NCB-RI) to address the message dissemination at road intersection. Considering each BSM packet broadcast occupies one broadcast slot, our objective is to reduce the required number of broadcast slots and lower the total transmission time for exchanging all BSMs among the studied vehicles. The coding overhead caused by the random linear network coding is further deducted by using coefficient seeds. The upper bounds regarding the broadcast slots for both NCB-RI and traditional broadcast scheme without network coding are discussed. Our proposed NCB-RI outperforms the traditional solution which is verified by analysis and simulations.

Network coding has become increasingly popular in time efficient data dissemination due to its inherent nature of broadcasting multiple data items in encoded form through a single broadcast. However, not much attention has been put forth on the efficiency of network coding when accessed data items' sizes can vary. In this work, we have investigated that when clients' accessed data items are of different sizes, network coding based broadcast can no longer maintain its superiority over traditional broadcast. We have found the reason of this performance degradation of coding based broadcast and propose an efficient dynamic threshold based coding approach. The proposed approach can maintain its performance superiority over both traditional broadcast approach and conventional coding based approach under a range of different size accessed data items. Simulation results support our claim.

Low Power and Lossy Networks (LLNs), as it covers a wide scope of applications, such as building automation, industrial control, healthcare etc., has received considerable attention in recent years. In many LLNs applications, Point-to-point (P2P) communication is crucial, which extremely need to be supported by reliable and energy- efficient routing protocols. However, traditional routing protocols usually propagate the whole network to discover a reliable P2P route, causing a huge energy consumption. Moreover, it is a critical but difficult task to achieve the requirements of reliability and energy efficiency at the same time in LLNs. Therefore, in this paper, in order to address the above challenges, we propose a novel energy-efficient region-based routing protocol, called ER-RPL, which attains an energy-efficient data delivery without compromising the reliability. In contrast of traditional routing protocols where all the nodes are required for route discovery, in ER-RPL only a subset of nodes are required to participate in the job, which is the key to energy conservation. Extensive simulations are conducted, and the results demonstrate that ER-RPL has a great performance superiority over two benchmark protocols, i.e., RPL and P2P-RPL.

Routing plays an important role in the overall architecture of the Internet of Things. IETF has standardized the RPL routing protocol to provide the interoperability for low-power and lossy networks (LLNs). LLNs cover a wide scope of applications, such as building automation, industrial control, healthcare, and so on. LLNs applications require reliable and energy-efficient routing support. Point-to-point (P2P) communication is a fundamental requirement of many LLNs applications. However, traditional routing protocols usually propagate throughout the whole network to discover a reliable P2P route, which requires large amount energy consumption. Again, it is challenging to achieve both reliability and energy-efficiency simultaneously, especially for LLNs. In this paper, we propose a novel energy-efficient region-based routing protocol (ER-RPL), which achieves energy-efficient data delivery without compromising reliability. In contrast of traditional routing protocols where all nodes are required for route discovery, the proposed scheme only requires a subset of nodes to do the job, which is the key of energy saving. Our theoretical analysis and extensive simulation studies demonstrate that ER-RPL has a great performance superiority over two conventional benchmark protocols, i.e., RPL and P2P-RPL.

Many safety and non-safety related applications have been envisioned in VANETs . However, efficient data dissemination considering the mobility of vehicle is must for the success of these applications. Although the Road Side Unit (RSU) is a stationary unit, both RSU and vehicle have limited transmission range that restricts to shorter connection time. This endures a higher request drop rate especially at the overloaded RSUs. A cooperative load balancing (CLB) among the RSUs to use their residual bandwidth can be an effective solution to reduce the request drop rate. In this paper, we investigate that considering the remaining delay tolerance of submitted requests and the knowledge of fixed road layout, the performance of the cooperative load balancing system can be further improved significantly. We show that this performance gain comes from serving the requests based on the urgency and the efficient load balancing among the junction-RSUs and edge-RSUs. Based on the observations, we propose an Enhanced CLB (ECLB) approach in this paper. To demonstrate the efficiency of the ECLB approach a number of well-known scheduling algorithms are integrated and an extensive simulation experiments are conducted in the vehicular communication environment that supports the superiority of ECLB over the existing approaches.

It is challenging to design a routing scheme that can successfully operate in the presence of adversarial environment in mobile ad hoc network (MANET), where several types of severe routing security threats can be easily employed against normal routing. Among them, active black hole attack is a typical one. Most existing defense schemes postulated that active black hole attackers have no knowledge about the internal prevention mechanisms of MANETs. However, due to the open and self-organized nature of MANET, it is necessary to assume that all nodes, including attackers, know how the security mechanism works. In this paper, we propose a distributed self-checking scheme that can effectively prevent various forms of active black hole attackers. Even the internal attackers who know the security mechanism cannot get any benefit to launch those attacks. Simulation results affirm that our proposed solution is robust and able to improve the packet delivery ratio significantly in an adversarial MANET environment as compared with other routing schemes. Copyright © 2015 John Wiley & Sons, Ltd.

This paper develops a comprehensive analytical framework with foundations in stochastic geometry to characterize the performance of cluster-centric content placement in a cache-enabled device-to-device (D2D) network. Different from device-centric content placement, cluster-centric placement focuses on placing content in each cluster, such that the collective performance of all the devices in each cluster is optimized. Modeling the locations of the devices by a Poisson cluster process, we define and analyze the performance for three general cases: 1) k-Tx case: the receiver of interest is chosen uniformly at random in a cluster and its content of interest is available at the kth closest device to the cluster center; 2) 1-Rx case: the receiver of interest is the Ith closest device to the cluster center and its content of interest is available at a device chosen uniformly at random from the same cluster; and 3) baseline case: the receiver of interest is chosen uniformly at random in a cluster and its content of interest is available at a device chosen independently and uniformly at random from the same cluster. Easy-to-use expressions for the key performance metrics, such as coverage probability and area spectral efficiency of the whole network, are derived for all three cases. Our analysis concretely demonstrates significant improvement in the network performance when the device on which content is cached or device requesting content from cache is biased to lie closer to the cluster center compared with the baseline case. Based on this insight, we develop and analyze a new generative model for cluster-centric D2D networks that allows to study the effect of intra-cluster interfering devices that are more likely to lie closer to the cluster center.

In this paper, we consider the wireless broadcasting scenario with a source node sending some common information to a group of closely located users, where each link is subject to certain packet erasures. To ensure reliable information reception by all users, the conventional approach generally requires repeated transmission by the source until all the users are able to decode the information, which is inefficient in many practical scenarios. In this paper, by exploiting the close proximity among the users, we propose a novel two-phase wireless broadcasting protocol with user cooperations based on an efficient batched network code, known as batched sparse (BATS) code. In the first phase, the information packets are encoded into batches with BATS encoder and sequentially broadcasted by the source node until certain terminating criterion is met. In the second phase, the users cooperate with each other by exchanging the network-coded information via peer-to-peer (P2P) communications based on their respective received packets. A fully distributed and light-weight scheduling algorithm is proposed to improve the efficiency of the P2P communication in the second phase. The performance of the proposed two-phase protocol is analyzed and the channel rank distribution at the instance of decoding is derived, based on which the optimal BATS code is designed. Simulation results show that the proposed protocol outperforms most existing cooperative packet exchange schemes, especially when the inter-user links are not reliable. Lastly, the performance of the proposed scheme is further verified via testbed experiments.

Device-to-device (D2D) communication enables direct communication between proximate devices thereby improving the overall spectrum utilization and off-loading traffic from cellular networks. This paper develops a new spatial model for D2D networks in which the device locations are modeled as a Poisson cluster process. Using this model, we study the performance of a typical D2D receiver in terms of coverage probability under two realistic content availability setups: 1) content of interest for a typical device is available at a device chosen uniformly at random from the same cluster, which we term uniform content availability, and 2) content of interest is available at the kthclosest device from the typical device inside the same cluster, which we term k-closest content availability. Using these coverage probability results, we also characterize the area spectral efficiency (ASE) of the whole network for the two setups. A key intermediate step in this analysis is the derivation of the distributions of distances from a typical device to both the intra-and inter-cluster devices. Our analysis reveals that an optimum number of D2D transmitters must be simultaneously activated per cluster in order to maximize ASE. This can be interpreted as the classical tradeoff between more aggressive frequency reuse and higher interference power. The optimum number of simultaneously transmitting devices and the resulting ASE increase as the content is made available closer to the receivers. Our analysis also quantifies the best and worst case performance of clustered D2D networks both in terms of coverage and ASE.

Interference field in wireless networks is often modeled by a homogeneous Poisson point process (PPP). While it is realistic in modeling the inherent node irregularity and provides meaningful first-order results, it falls short in modeling the effect of interference management techniques, which typically introduces some form of spatial interaction among active transmitters. In some applications, such as cognitive radio and device-to-device networks, this interaction may result in the formation of holes in an otherwise homogeneous interference field. The resulting interference field can be accurately modeled as a Poisson hole process (PHP). Despite the importance of the PHP in many applications, the exact characterization of interference experienced by a typical node in the PHP is not known. In this paper, we derive several tight upper and lower bounds on the Laplace transform of this interference. Numerical comparisons reveal that the new bounds outperform all known bounds and approximations, and are remarkably tight in all operational regimes of interest. The key in deriving these tight and yet simple bounds is to capture the local neighborhood around the typical node accurately while simplifying the far field to attain tractability. Ideas for tightening these bounds further by incorporating the effect of overlaps in the holes are also discussed. These results immediately lead to an accurate characterization of the coverage probability of the typical node in the PHP under Rayleigh fading.

Low-Power and Lossy networks (LLNs) cover a wide scope of applications, including, but not limit to, industrial control, healthcare and building automation, which has proliferated into both industrial and academic areas in recent years. Routing plays a significant role to the overall architecture of LLNs. The IPv6 Routing Protocol for Low Power and Lossy Networks (RPL) is standardized by IETF to provide interoperability for LLNs. Traditional routing protocols deliver packets through single relay and cannot cope well with the unreliable wireless medium. In this paper, we propose a cluster-parent based RPL protocol (CRPL), which is an opportunistic coordination forwarding scheme. In CRPL, through a top-down approach, an optimization problem is formulated. And the optimal cluster-parent set is selected to minimize the end-to-end cost for individual node. Priority-based scheduling mechanism is applied to coordinate the cluster-parent set for packet forwarding. We compare CRPL with RPL, and another recent work, ORPL on NS3 platform. The performance metrics in terms of packet delivery ratio, number of retransmission and average path cost are measured under various scenarios. Simulation results show that CRPL outperforms RPL and ORPL with significant improvement on the network reliability and reduction of packet retransmission.

This paper develops a new spatial model for device-to-device (D2D) networks in which the device locations are modeled as a Thomas cluster process. The devices inside a given cluster form D2D links amongst themselves and the direct communication across clusters is not required. This model captures the fact that the devices engaged in D2D communications need to be in close proximity of each other. For this model, we derive easy-to-use expressions for both coverage probability and area spectral efficiency (ASE) assuming that the content of interest is available at a device chosen uniformly at random from the same cluster. One of the important consequences of this analysis is that there exists an optimal number of simultaneously active D2D-Txs that maximizes the ASE. This can be interpreted as the classical tradeoff between more aggressive frequency reuse and higher interference power. Our analysis also provides insights into the effect of scattering variance of each cluster and the density of cluster centers on coverage probability and ASE.

The design issues of resource constrained sensor network include the use of efficient routing protocol which have significant impact on the energy dissipation of the network. Since the energy saving plays the main challenge in the design and implementation of wireless sensor networks, we proposed the energy efficient routing protocol which is an integration of clustering and routing in sensor network. In our approach, we also performed network coding during the data routing in order to achieve the additional power saving in the cluster head nodes. Simulation results are provided to show the efficacy of the proposed method in terms of the throughput and end-to-end delay. In addition, the results show significant improvement of proposed method in the network lifetime over other technique.

MOTIVATION: The arbor morphologies of brain microglia are important indicators of cell activation. This article fills the need for accurate, robust, adaptive and scalable methods for reconstructing 3-D microglial arbors and quantitatively mapping microglia activation states over extended brain tissue regions. RESULTS: Thick rat brain sections (100-300 µm) were multiplex immunolabeled for IBA1 and Hoechst, and imaged by step-and-image confocal microscopy with automated 3-D image mosaicing, producing seamless images of extended brain regions (e.g. 5903 × 9874 × 229 voxels). An over-complete dictionary-based model was learned for the image-specific local structure of microglial processes. The microglial arbors were reconstructed seamlessly using an automated and scalable algorithm that exploits microglia-specific constraints. This method detected 80.1 and 92.8% more centered arbor points, and 53.5 and 55.5% fewer spurious points than existing vesselness and LoG-based methods, respectively, and the traces were 13.1 and 15.5% more accurate based on the DIADEM metric. The arbor morphologies were quantified using Scorcioni's L-measure. Coifman's harmonic co-clustering revealed four morphologically distinct classes that concord with known microglia activation patterns. This enabled us to map spatial distributions of microglial activation and cell abundances. AVAILABILITY AND IMPLEMENTATION: Experimental protocols, sample datasets, scalable open-source multi-threaded software implementation (C++, MATLAB) in the electronic supplement, and website (www.farsight-toolkit.org). http://www.farsight-toolkit.org/wiki/Population-scale_Three-dimensional_Reconstruction_and_Quanti-tative_Profiling_of_Microglia_Arbors CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

In this paper, we propose a new routing protocol called hybrid opportunistic routing (HOR) which takes the advantage of broadcast nature of wireless medium and replication-based data forwarding. The data packets are transmitted by broadcast-based forwarding if the destination node is within two-hop distance from sender or by replication-based forwarding otherwise. By exploiting overhearing opportunity, nodes can build up knowledge about data packets. The adaptive nature of data forwarding and overhearing capability provide high data delivery with minimum buffer requirement in highly dynamic MANET. Simulation results prove that 1) proposed scheme increases data delivery by above 30% compared to traditional MANET routing and 2) it can achieve 98% data delivery with 17% of the total packets for buffer space compared to replication-based routing which requires 50% of the total packets for buffer space to maintain 89% of data delivery.

We propose a dynamic interference mitigation technique by incorporating cognitive capability and cooperative mechanism in two tier heterogeneous network (HetNet) with open access femtocells. To further enhance protection of victim user that is subject to interference, a cooperative mechanism is designed based on received power of user. We exploit stochastic geometry for modelling and analysing the effect of our interference mitigation mechanism in two-tier HetNet by considering Rayleigh fading environment. Results show significant improvement on the coverage probability.

There has been an increasing interest in deploying wireless mesh networks (WMNs) for communication and video surveillance purposes thanks to its low cost and ease of deployment. It is well known that a major drawback of WMN is multihop bandwidth degradation, which is primarily caused by contention and radio interference. The use of mesh nodes with multiple radios and channels has been regarded as a straightforward solution to the problem in the research community. However, we demonstrate in this paper through real-world experiments that such an approach cannot resolve the multihop TCP throughput degradation problem in IEEE 802.11n mesh networks. With extensive experimentation, we verify that the degradation is principally caused by the increase in TCP Round-Trip Time (RTT) when the number of hops increases. TCP throughput is fundamentally limited inversely by the RTT. We find that the multihop TCP throughput (up to five hops) when using 802.11n is no better than when using 802.11a, despite the much higher data rate 802.11n. We attempt to use multiple parallel TCP connections as a remedy to the problem, and it turns out that the wireless bandwidth can be fully utilized with a sufficient number of parallel streams. In general, our results give a key message that TCP tuning (e.g., setting the correct TCP buffers and use of parallel streams) is of paramount importance in high-bandwidth multihop wireless mesh networks that employ the latest wireless standards. These tuning techniques have to be implemented into commercial products to fully leverage the ever advancing wireless technologies to support the growing demand of multihop communications in wireless mesh networks.

As a challenged network, the delay-tolerant network (DTN) generally has unpredictable delay for the packet delivery due to the insufficiency of the network connectivity. Thus, it is inadequate to support some time-sensitive applications. In this paper we aim to mitigate this unpredictability of the delay in DTN to broaden its applications by proposing a new routing strategy to make use of the node mobility. Our designed solution is called purpose-movement assisted routing (PMAR) aiming for a more realistic mobility model, group mobility, which has been paid attention in many realistic scenarios. Different from the traditional store-carry-forward DTN routing strategy, in which nodes wait for the connectivity passively, PMAR employs nodes to actively create new connection by altering the node movement, and thus the packet could be delivered in an expedited manner. More importantly, the proposed PMAR could be taken as a component to be integrated into different DTN routings for group mobility to make them more aggressive in delivering packets. In this paper, we integrate PMAR into a previously proposed routing, group-epidemic routing (G-ER). PMAR could be triggered whenever some packets need to be delivered to the destinations in a faster way, but without any connection to their destinations. By computer simulation, it is found that PMAR could greatly improve G-ER, especially the packet delay.

In this paper we propose a new routing scheme called group-epidemic routing (G-ER), which is specifically designed for group mobility in mobile ad hoc networks. G-ER is based on one proposed delay tolerant routing protocol called epidemic routing (ER). So, it could tolerate the disconnection characteristic among groups in group mobility. By considering each group as a single node, G-ER has made a great improvement to ER, which is shown in the simulation. In addition, we introduce the buffer sharing mechanism inside each group for G-ER. Also, the simulation has demonstrated the effectiveness of the buffer sharing mechanism, especially in a more disconnected scenario for group mobility.

While Two-Way Ranging (TWR) is generating interest as a accurate and low-cost indoor localization technique, most TWR research focuses primarily on algorithms or error reduction, with little regard to a fundamental system-level issue: deciding which Base Stations (BS) should perform the TWR. While most researchers acknowledge the need for a scanning phase to select BSs before the ranging phase is carried out, this scanning phase has not been explored in detail. In that regard, we utilize Received Signal Strength Indicator (RSSI) as the basis for BS selection. RSSI is a measure of the signal strength of an incoming radio packet, and is found on virtually every Radio Frequency (RF) transceiver, making its use almost free of additional hardware cost. While RSSI measurements are unreliable in indoor environments and cannot be practically used for localization, we show that RSSI is a reliable indicator for the scanning phase and BS selection. More specifically, we develop a Distributed RSSI-Sharing technique to efficiently select BSs and create a simulation to test this technique. We implement and test technique on actual hardware with good results and finally propose RSSI-smoothing and a BS-Reduction method to improve the performance.

Continuous growth of cellular subscribers as well as demands for high-speed and high-quality multimedia services have made it necessary to increase system capacity and data rate. On the other hand, the energy consumed goes up accordingly as the data rates increases. Therefore, designing an efficient resources allocation scheme and architecture to improve the output performance and reduce energy consumption will be the focus for future research. In this paper, we propose an opportunistic relay selection technique to save energy consumption for future Green multihop cellular networks. Then, we developed a comprehensive simulation model with consideration of path loss, shadowing, inter-cell and intra-cell interference and other service requests for both single hop and multi-hop TDD-CDMA based cellular system to conduct a deep investigation of energy consumption including the hardware energy for different RS selection under various time slot allocation schemes.

Ad hoc routing protocols can be divided into flat and hierarchical routing. One typical way to build hierarchy is to group mobile nodes into clusters, thus decrease routing space and improve network performance. Mobility models also affect the performance of ad hoc routing protocols and can be divided into entity mobility and group mobility models. This paper first studies the performance of flat routing, AODV and DSR, and cluster-based hierarchical routing, CBRP and ECBRP, on entity mobility, Random Waypoint, and group mobility, RPGM and RRGM. Performance comparisons between flat and cluster- based hierarchical routing protocols in different mobility models are analyzed. We have observed that the effects of group mobility on routing protocols are significantly different from that of entity mobility.

Multihop TDD-CDMA cellular system becomes a promising candidate for fourth generation (4G) cellular systems because it provides wider coverage and higher throughput. In this paper, we analyze the uplink system capacity of a multihop TDD-CDMA cellular system. We first analyze a one-hop TDDCDMA cellular system with different base station's (BS's) direct coverage area. We find that the system capacity can be improved if a BS only covers a center small area of the cell. Besides, the high downlink transmission power of the surrounding BSs can degrade the capacity severely. Thus, we propose a multihop TDD-CDMA cellular system to overcome the high downlink inter-cell interference. In our system, a cell area is divided into two regions: inner-region and outer-region. The mobile users in the inner- and outer- region of the cell communicate with BS and relay station (RS), respectively. Based on this model, the uplink system capacity in both regions with the assumption that the inter-cell and intra-cell interference follow the Gaussian distribution is obtained. A comparison equation to provide a fair comparison with conventional one-hop TDD-CDMA cellular system is presented. From the results, we conclude that multihop TDD-CDMA cellular system can improve capacity significantly.

In this paper, we propose a multihop medium access control (mMAC) scheme for time division duplexing-code division multiple access (TDD-CDMA) cellular networks with two-hop relay architecture to support packet data transmission. The proposed mMAC is based on joint CDMA/PRMA (packet reservation multiple access) protocol and it includes BCH code selection, power control and multihop relaying. Simulation results reveal that cellular networks with two-hop relay architecture with the proposed mMAC scheme can substantially provide a good performance as well as larger cell coverage as compared to conventional TDD-CDMA single-hop cellular networks.

This paper first implements routing mechanisms in cluster based routing protocol (CBRP) on a recently proposed clustering scheme, named efficient clustering scheme (ECS). Such a cluster based routing scheme is named efficient cluster based routing protocol (ECBRP) in this paper. ECS maintains a more stable and less overlapping 1-hop clusterhead-based cluster structure as compared to other typical clustering schemes, such as Least Clusterhead Change (LCC) used in CBRP, and hence is more efficient in simplifying a network structure. Some routing mechanisms in CBRP are modified accordingly in order to make full use of the underlying cluster structure maintained by ECS. Also, an information table update mechanism by utilizing routing and data forwarding events to enhance the clustering and routing performance is proposed. The complete routing performance of ECBRP in terms of packet delivery ratio, normalized routing overhead and end-to-end transmission delay is compared with that of CBRP and DSR. By evaluating the performance of ECBRP and CBRP, we can study how the performance of a cluster based routing protocol is affected by its underlying cluster structure, including cluster stability and cluster overlapping. Simulation results show that ECBRP can achieve satisfying routing performance under the simulated scenarios.

In this paper, we propose a multihop dynamic channel assignment (MDCA) scheme for time division multiple access (TDMA)-based multihop cellular networks. The proposed MDCA assigns channels to calls based on interference information in surrounding cells, provided by the interference information table (IIT) in the network. Two different channel searching strategies, Sequential channel searching (SCS) and packing-based channel searching (PCS), for use in MDCA are proposed and studied. A channel reassignment procedure to further enhance the performance is also investigated. Simulation results show that MDCA significantly improves the system capacity. Furthermore, the MDCA can efficiently alleviate the call blocking in hot-spot cells.

Abstract Whereas cellular systems have traditionally adopted single‐hop transmissions between the mobile station (MS) and the base station (BS), researchers expect multihop transmission to be utilised in the future. Cellular systems present several challenges, such as channel assignment, which are exacerbated by multimedia service traffic and an increasing number of subscribers. Recently, a clustered multihop cellular network (cMCN) architecture that complements traditional cellular systems has been proposed and studied using fixed channel assignment (FCA). However, the performance of FCA is limited when the traffic pattern varies in a service area. This paper proposes the use of dedicated information ports (DIPs) as clusterheads in cMCN, followed by a multihop dynamic channel assignment (mDCA) scheme. The mDCA works by assigning channels based on information about interference in surrounding cells. Two different channel searching strategies are developed and evaluated. Through computer simulation, we show that the proposed mDCA is able to achieve a significantly improved capacity which is maintained when the number of system channels is increased. Finally, issues regarding the implementation of the mDCA and future work on this topic are discussed. Copyright © 2007 John Wiley & Sons, Ltd.

Abstract In this paper, we study the blocking and dropping probability of mobile users in the multi‐service cellular systems with mobile users. Based on the idea that different services may require different signal‐to‐interference ratios and different reuse factors, we proposed a channel allocation scheme calledchannel partitioningto support different services using different reuse factors. Under channel partitioning scheme, the channels in each cell are divided into two or more sets of channels and each set of the channels supports certain service, depending on the required reuse factor of the service. We first apply this channel partitioning with fixed channel allocation scheme called fixed channel partitioning (FCP), where a three‐dimensional Markov chain is developed to analyze the impact of the mobile user. After that a simpler model, which can estimate the numeric result from the closed‐form solution, is presented to make the analysis easier. In order to cater for the traffic variation between services and between cells, a dynamic channel partitioning with flexible channel combination scheme, called FDCP, is proposed to support multiple services. This FDCP tries to minimize the effect of assigned channels on the availability of channels for use in the interfering cells. The analysis and the simulation results show that for equal arrival rate of two services, the proposed FCP and FDCP scheme can provide about 32% and 54% improvement, respectively, in terms of grade of service as compared with conventional FCA scheme using a single reuse factor to support two services for the mobile users. Copyright © 2006 John Wiley & Sons, Ltd.

In UMTS terrestrial radio access (UTRA) standard, each frame consists of 15 TSs for TDD-CDMA system. Any MS can be allocated to any TS for either uplink or downlink transmission. The time slot allocation scheme within these 15 TSs gives the system the freedom of adapting the channel environment. In this paper, we propose and study multihop dynamic time slot allocation schemes, namely dynamic switching point with multihop (DSPM) and maximum interference first (MIF), for TDD-CDMA system. Compared to slot allocation schemes without multihop technique, it is shown that our proposed schemes can improve both the data rate for single user and the overall throughput for the whole system. In addition, we also study the distribution of data transmission speed to demonstrate the effectiveness of each slot allocation scheme clearly.

Multihop cellular network (MCN) has been proposed to incorporate the flexibility of ad hoc networks into traditional cellular networks. Little work has been reported on the channel assignment for MCN. In this paper, we investigate the feasibility of applying the characteristics of the hierarchical overlaid microcell/macrocell architecture and the clustering of MANETs for channel assignment in TDMA-based MCN. Based on our deliberated clustered MCN (cMCN) structure with virtual microcells, we propose a fixed channel assignment (FCA) scheme for uplink transmission. An exact Markov chain model is developed to analyze its performance. In addition, an approximated model, which can reduce the computational load greatly, with much fewer states is also found. The analytical models are validated through computer simulation. From the results, our proposed FCA scheme can reduce the call blocking probability significantly as compared with the FCA for conventional single-hop cellular system. The salient contribution is that our proposed FCA scheme can increase the spectrum efficiency and the system capacity without increasing infrastructure cost by introducing the structure of cMCN with virtual microcells. We also provide some recommendations for future work on this topic.

In this paper, we study the performance of mobile users, in terms of call blocking and dropping probabilities, with our proposed idea of channel partitioning (CP). CP is based on the fact that different services may require different signal-to-interference ratios, and thus different reuse factors. We apply this CP with fixed channel allocation (FCA) scheme called fixed channel partitioning (FCP) in cellular systems. With FCP scheme, each cell is allocated two or more sets of channels. Each set of the channels supports a service in the way that the required reuse factor for that service could be satisfied. A three-dimensional Markov chain is first developed to analyze the impact of the mobile user. Then a simpler model, which can be used to estimate the numeric results from the closed-form solution, is presented to make the analysis easy. Finally, the analytical results are verified with simulation results. The results of this paper show that, for equal voice and data call arrival rate, the proposed FCP scheme can provide about 32% capacity improvement at 1% grade of service (GoS) as compared with FCA scheme. The changing of mobile speed and GoS factor do not affect this improvement. Our proposed FCP scheme could apply in current GSM, GPRS EDGE and future cellular OFDM systems, in which reuse factor plays a very important role.

In this paper, we propose flexible dynamic channel partitioning (FDCP) with a flexible channel-combination scheme to support multiple services. CP is based on the idea that different services may require different signal-to-interference ratios (SIRs), and thus, different reuse factors. In FDCP, different services are allocated to the channels depending on the reuse factors they require. FDCP tries to minimize the effect of the assigned channels on the channel availability to the interfering cells and to reduce the overall reuse distances of the systems.

In cellular communications, how to achieve optimum system capacity with limited frequency spectrum is one of the main research issues. Many dynamic channel assignment (DCA) schemes have been proposed and studied to increase the capacity of cellular systems. Reuse partitioning (RP) is another technique to achieve higher capacity by reducing the overall reuse distance. In convention, when RP is exploited in DCA, a portion of channels are assigned permanently to each partitioned region (A. Pattavina et al., 1999 and Steve I. Chen et al., Sept. 2003). However, the number of channels assigned to each region may not be optimum due to the uneven and time-varying traffic. In this paper, a new network-based DCA scheme with the flexible use of RP technique is proposed, namely flexible dynamic reuse partitioning with interference information (FDRP-WI). In this scheme, channels are open to all incoming calls and no channel allocation for each region is required. As long as the assignment satisfies the co-channel interference constraints, any user from different regions can use any channel. The scheme aims to minimize the effect of assigned channels on the availability of channels for use in the interfering cells and to reduce their overall reuse distances. Simulation results have confirmed the effectiveness of FDRP-WI scheme. Under both uniform and nonuniform traffic distributions, FDRP-WI exhibits outstanding performance in improving the system capacity. It can provide over 100% capacity improvement as compared to conventional fixed channel assignment scheme with 70 system channels at 1% blocking probability.

Due to the limited spectrum in wireless communication cellular systems, channel allocation scheme is a very important issue to achieve high system capacity. In this paper, we present an efficient algorithm using the idea of channel partitioning (CP) to support two types of services requiring different reuse factors. CP is based on the fact that different service requires different SIR and thus can use different reuse factor. A higher SIR required service might use a larger reuse factor while a lower SIR required service might use a smaller reuse factor. We apply this CP algorithm to a previous proposed DCA scheme, DCA-WI. Our newly proposed dynamic channel partitioning with interference information (DCP-WI) tries to manage the channel allocation in a proper way between cells so that each allocation of the channel causes least interference to the neighboring cells. The simulation results show that DCP-WI outperforms FCA and DCA-WI under both uniform and nonuniform traffic distributions.

In cellular mobile communications, how to achieve optimum system capacity with limited frequency spectrum is one of the main research issues. Many dynamic channel assignment (DCA) schemes have been proposed and studied to increase the capacity of cellular systems. Reuse partitioning (RP) is another technique to achieve higher capacity by reducing the overall reuse distance. In this paper, a new network-based DCA scheme with the use of RP technique is proposed, namely dynamic reuse partitioning with interference information (DRP-WI). The scheme aims to minimize the effect of assigned channels on the availability of channels for use in the interfering cells and to reduce their overall reuse distances. Simulation results have confirmed the effectiveness of DRP-WI scheme. Under both uniform and nonuniform traffic distributions, DRP-WI exhibits outstanding performance in improving the system capacity. It can provide about 100% capacity improvement as compared to conventional fixed channel assignment scheme.

The high-speed downlink packet access (HSDPA) is currently an important research topic to enhance the downlink performance of a WCDMA network. It is a set of schemes built on top of the downlink shared channel (DSCH), resulting an extremely high bit rate for a single user in the downlink. When the channel condition is good, a high utilization of the code resource for a single user can be effectively achieved. However, when the channel condition is bad, a fraction of the code resource would be wasted because only a user can use a small fraction of the code resource. Thus, code multiplexing offers a solution to utilize the limited code resource more effectively. In this paper, the effect of code multiplexing on the HSDPA performance is studied in a dynamic simulator platform. It means that the code resource is shared among a few users. Multicode transmission is also considered in the study. Two, semi-static and dynamic code sharing, multiplexing cases are studied. The number, n, of the code multiplexing users is one of the study parameters. The simulation results show that code-multiplexing can increase the throughput in a WCDMA network by improving code utilization while also decreasing the transfer delay between the base station and the terminals.

An expression for the bit-error rate (BER) of noncoherent frequency-shift keying with a nonfaded desired signal in the presence of N Rayleigh-faded unsynchronized cochannel interferers (UCCIs) and additive white Gaussian noise is first derived. This result can be used to obtain the BER for a faded desired signal. For a large number of UCCIs, numerical evaluation of this expression can be quite time-consuming. An approximate method that yields fairly accurate results is thus described. Numerical results show that for a Rician-faded desired signal with a strong specular component in an interference-limited environment, the BER decreases slightly with N whereas for a Rayleigh-faded desired signal, the BER varies very little with N. A comparison to the BER performance with synchronized cochannel interferers is also provided.

Reuse partitioning (RP) is a simple technique that can be used to increase system capacity. With RP, a cell is divided into several concentric regions, each associated with a different cluster size. In this paper, a traffic model is developed to analyze the impact of mobile users on an RP with fixed channel assignment system. The influence of user speed and cell size on the new call blocking probability, P/sub b/, and the call dropping probability, P/sub d/, is investigated. A simpler model which can be used to estimate P/sub b/ and P/sub d/ in some cases is described. The effect of reserving some channels for handoff calls on the capacity is studied. It is found that even though prioritized handoff can reduce P/sub d/, it may also degrade the capacity.