Reliable Message Dissemination in Mobile Vehicular Networks

Les réseaux véhiculaires accueillent une multitude d’applications d’info-divertissement et de sécurité. Les applications de sécurité visent à améliorer la sécurité sur les routes (éviter les accidents), tandis que les applications d’info-divertissement visent à améliorer l'expérience des passagers. Les applications de sécurité ont des exigences rigides en termes de délais et de fiabilité ; en effet, la diffusion des messages d’urgence (envoyés par un véhicule/émetteur) devrait être fiable et rapide. Notons que, pour diffuser des informations sur une zone de taille plus grande que celle couverte par la portée de transmission d’un émetteur, il est nécessaire d’utiliser un mécanisme de transmission multi-sauts. De nombreuses approches ont été proposées pour assurer la fiabilité et le délai des dites applications. Toutefois, ces méthodes présentent plusieurs lacunes. Cette thèse, nous proposons trois contributions. La première contribution aborde la question de la diffusion fiable des messages d’urgence. A cet égard, un nouveau schéma, appelé REMD, a été proposé. Ce schéma utilise la répétition de message pour offrir une fiabilité garantie, à chaque saut, tout en assurant un court délai. REMD calcule un nombre optimal de répétitions en se basant sur l’estimation de la qualité de réception de lien dans plusieurs locations (appelées cellules) à l’intérieur de la zone couverte par la portée de transmission de l’émetteur. REMD suppose que les qualités de réception de lien des cellules adjacentes sont indépendantes. Il sélectionne, également, un nombre de véhicules, appelés relais, qui coopèrent dans le contexte de la répétition du message d’urgence pour assurer la fiabilité en multi-sauts. La deuxième contribution, appelée BCRB, vise à améliorer REMD ; elle suppose que les qualités de réception de lien des cellules adjacentes sont dépendantes ce qui est, généralement, plus réaliste. BCRB utilise les réseaux Bayésiens pour modéliser les dépendances en vue d’estimer la qualité du lien de réception avec une meilleure précision. La troisième contribution, appelée RICS, offre un accès fiable à Internet. RICS propose un modèle d’optimisation, avec une résolution exacte optimale à l'aide d’une technique de réduction de la dimension spatiale, pour le déploiement des passerelles. Chaque passerelle utilise BCRB pour établir une communication fiable avec les véhicules.Vehicular networks aim to enable a plethora of safety and infotainment applications. Safety applications aim to preserve people's lives (e.g., by helping in avoiding crashes) while infotainment applications focus on enhancing the passengers’ experience. These applications, especially safety applications, have stringent requirements in terms of reliability and delay; indeed, dissemination of an emergency message (e.g., by a vehicle/sender involved in a crash) should be reliable while satisfying short delay requirements. Note, that multi-hop dissemination is needed to reach all vehicles, in the target area, that may be outside the transmission range of the sender. Several schemes have been proposed to provide reliability and short delay for vehicular applications. However, these schemes have several limitations. Thus, the design of new solutions, to meet the requirement of vehicular applications in terms of reliability while keeping low end-to-end delay, is required. In this thesis, we propose three schemes. The first scheme is a multi-hop reliable emergency message dissemination scheme, called REMD, which guarantees a predefined reliability , using message repetitions/retransmissions, while satisfying short delay requirements. It computes an optimal number of repetitions based on the estimation of link reception quality at different locations (called cells) in the transmission range of the sender; REMD assumes that link reception qualities of adjacent cells are independent. It also adequately selects a number of vehicles, called forwarders, that cooperate in repeating the emergency message with the objective to satisfy multi-hop reliability requirements. The second scheme, called BCRB, overcomes the shortcoming of REMD by assuming that link reception qualities of adjacent cells are dependent which is more realistic in real-life scenarios. BCRB makes use of Bayesian networks to model these dependencies; this allows for more accurate estimation of link reception qualities leading to better performance of BCRB. The third scheme, called RICS, provides internet access to vehicles by establishing multi-hop reliable paths to gateways. In RICS, the gateway placement is modeled as a k-center optimisation problem. A space dimension reduction technique is used to solve the problem in exact time. Each gateway makes use of BCRB to establish reliable communication paths to vehicles

Achieving reliable and enhanced communication in vehicular ad hoc networks (VANETs)

A thesis submitted to the University of Bedfordshire in partial fulfilment of the requirement for the degree of Doctor of PhilosophyWith the envisioned age of Internet of Things (IoTs), different aspects of Intelligent Transportation System (ITS) will be linked so as to advance road transportation safety, ease congestion of road traffic, lessen air pollution, improve passenger transportation comfort and significantly reduce road accidents. In vehicular networks, regular exchange of current position, direction, speed, etc., enable mobile vehicle to foresee an imminent vehicle accident and notify the driver early enough in order to take appropriate action(s) or the vehicle on its own may take adequate preventive measures to avert the looming accident. Actualizing this concept requires use of shared media access protocol that is capable of guaranteeing reliable and timely broadcast of safety messages. This dissertation investigates the use of Network Coding (NC) techniques to enrich the content of each transmission and ensure improved high reliability of the broadcasted safety messages with less number of retransmissions. A Code Aided Retransmission-based Error Recovery (CARER) protocol is proposed. In order to avoid broadcast storm problem, a rebroadcasting vehicle selection metric η, is developed, which is used to select a vehicle that will rebroadcast the received encoded message. Although the proposed CARER protocol demonstrates an impressive performance, the level of incurred overhead is fairly high due to the use of complex rebroadcasting vehicle selection metric. To resolve this issue, a Random Network Coding (RNC) and vehicle clustering based vehicular communication scheme with low algorithmic complexity, named Reliable and Enhanced Cooperative Cross-layer MAC (RECMAC) scheme, is proposed. The use of this clustering technique enables RECMAC to subdivide the vehicular network into small manageable, coordinated clusters which further improve transmission reliability and minimise negative impact of network overhead. Similarly, a Cluster Head (CH) selection metric ℱ(\u1d457) is designed, which is used to determine and select the most suitably qualified candidate to become the CH of a particular cluster. Finally, in order to investigate the impact of available radio spectral resource, an in-depth study of the required amount of spectrum sufficient to support high transmission reliability and minimum latency requirements of critical road safety messages in vehicular networks was carried out. The performance of the proposed schemes was clearly shown with detailed theoretical analysis and was further validated with simulation experiments

Performance evaluation of networking protocols for connected vehicles

Modern cars feature many embedded systems that monitor and manage all the critical sensors and actuators. The interconnection of such systems is a challenging task since the information to be exchanged is of mission-critical nature and affects the driving experience. The vehicle connectivity can be further extended with Vehicle-to-Vehicle (V2V) technology, which allows cars to exchange sensory information and even act on it. In this article a unified networking architecture is presented, starting from the inside of the vehicle and the interconnection of various control units and ultimately targeting Car-to-Car communications which enable smarter, safer and more efficient transportation. The researchers review and evaluate the performance of Power Line Communications as a solution for in-car networking. Then the safety-critical data as well as multimedia originating from each individual vehicle's in-car network are broadcasted to other neighbouring vehicles via IEEE 802.11p in a simulation environment featuring realistic vehicular mobility

Optimisation of Mobile Communication Networks - OMCO NET

The mini conference “Optimisation of Mobile Communication Networks” focuses on advanced methods for search and optimisation applied to wireless communication networks. It is sponsored by Research & Enterprise Fund Southampton Solent University. The conference strives to widen knowledge on advanced search methods capable of optimisation of wireless communications networks. The aim is to provide a forum for exchange of recent knowledge, new ideas and trends in this progressive and challenging area. The conference will popularise new successful approaches on resolving hard tasks such as minimisation of transmit power, cooperative and optimal routing

Performance modelling of adaptive VANET with enhanced priority scheme

In this paper, we present an analytical and simulated study on the performance of adaptive vehicular ad hoc networks (VANET) priority based on Transmission Distance Reliability Range (TDRR) and data type. VANET topology changes rapidly due to its inherent nature of high mobility nodes and unpredictable environments. Therefore, nodes in VANET must be able to adapt to the ever changing environment and optimize parameters to enhance performance. However, there is a lack of adaptability in the current VANET scheme. Existing VANET IEEE802.11p’s Enhanced Distributed Channel Access; EDCA assigns priority solely based on data type. In this paper, we propose a new priority scheme which utilizes Markov model to perform TDRR prediction and assign priorities based on the proposed Markov TDRR Prediction with Enhanced Priority VANET Scheme (MarPVS). Subsequently, we performed an analytical study on MarPVS performance modeling. In particular, considering five different priority levels defined in MarPVS, we derived the probability of successful transmission, the number of low priority messages in back off process and concurrent low priority transmission. Finally, the results are used to derive the average transmission delay for data types defined in MarPVS. Numerical results are provided along with simulation results which confirm the accuracy of the proposed analysis. Simulation results demonstrate that the proposed MarPVS results in lower transmission latency and higher packet success rate in comparison with the default IEEE802.11p scheme and greedy scheduler scheme

Computational Intelligence Inspired Data Delivery for Vehicle-to-Roadside Communications

We propose a vehicle-to-roadside communication protocol based on distributed clustering where a coalitional game approach is used to stimulate the vehicles to join a cluster, and a fuzzy logic algorithm is employed to generate stable clusters by considering multiple metrics of vehicle velocity, moving pattern, and signal qualities between vehicles. A reinforcement learning algorithm with game theory based reward allocation is employed to guide each vehicle to select the route that can maximize the whole network performance. The protocol is integrated with a multi-hop data delivery virtualization scheme that works on the top of the transport layer and provides high performance for multi-hop end-to-end data transmissions. We conduct realistic computer simulations to show the performance advantage of the protocol over other approaches

Enhancing the 3GPP V2X architecture with information-centric networking

Vehicle-to-everything (V2X) communications allow a vehicle to interact with other vehicles and with communication parties in its vicinity (e.g., road-side units, pedestrian users, etc.) with the primary goal of making the driving and traveling experience safer, smarter and more comfortable. A wide set of V2X-tailored specifications have been identified by the Third Generation Partnership Project (3GPP) with focus on the design of architecture enhancements and a flexible air interface to ensure ultra-low latency, highly reliable and high-throughput connectivity as the ultimate aim. This paper discusses the potential of leveraging Information-Centric Networking (ICN) principles in the 3GPP architecture for V2X communications. We consider Named Data Networking (NDN) as reference ICN architecture and elaborate on the specific design aspects, required changes and enhancements in the 3GPP V2X architecture to enable NDN-based data exchange as an alternative/complementary solution to traditional IP networking, which barely matches the dynamics of vehicular environments. Results are provided to showcase the performance improvements of the NDN-based proposal in disseminating content requests over the cellular network against a traditional networking solution119sem informaçãosem informaçã

Intelligent and bandwidth-efficient medium access control protocols for IEEE 802.11p-based Vehicular Ad hoc Networks

Vehicle-to-Vehicle (V2V) technology aims to enable safer and more sophisticated transportation via the spontaneous formation of Vehicular Ad hoc Networks (VANETs). This type of wireless networks allows the exchange of kinematic and other data among vehicles, for the primary purpose of safer and more efficient driving, as well as efficient traffic management and other third-party services. Their infrastructure-less, unbounded nature allows the formation of dense networks that present a channel sharing issue, which is harder to tackle than in conventional WLANs. This thesis focuses on optimising channel access strategies, which is important for the efficient usage of the available wireless bandwidth and the successful deployment of VANETs. To start with, the default channel access control method for V2V is evaluated hardware via modifying the appropriate wireless interface Linux driver to enable finer on-the-fly control of IEEE 802.11p access control layer parameters. More complex channel sharing scenarios are evaluated via simulations and findings on the behaviour of the access control mechanism are presented. A complete channel sharing efficiency assessment is conducted, including throughput, fairness and latency measurements. A new IEEE 802.11p-compatible Q-Learning-based access control approach that improves upon the studied protocol is presented. The stations feature algorithms that “learn” how to act optimally in VANETs in order to maximise their achieved packet delivery and minimise bandwidth wastage. The feasibility of Q-Learning to be used as the base of selflearning protocols for IEEE 802.11p-based V2V communication access control in dense environments is investigated in terms of parameter tuning, necessary time of exploration, achieving latency requirements, scaling, multi-hop and accommodation of simultaneous applications. Additionally, the novel Collection Contention Estimation (CCE) mechanism for Q-Learning-based access control is presented. By embedding it on the Q-Learning agents, faster convergence, higher throughput, better service separation and short-term fairness are achieved in simulated network deployments. The acquired new insights on the network performance of the proposed algorithms can provide precise guidelines for efficient designs of practical, reliable, fair and ultra-low latency V2V communication systems for dense topologies. These results can potentially have an impact across a range of related areas, including various types of wireless networks and resource allocation for these, network protocol and transceiver design as well as QLearning applicability and considerations for correct use

A Q-Learning approach with collective contention estimation for bandwidth-efficient and fair access control in IEEE 802.11p vehicular networks

Vehicular Ad hoc Networks (VANETs) are wireless networks formed of moving vehicle-stations, that enable safety-related packet exchanges among them. Their infrastructure-less, unbounded nature allows the formation of dense networks that present a channel sharing issue, which is harder to tackle than in conventional WLANs, due to fundamental differences of the protocol stack. Optimising channel access strategies is important for the efficient usage of the available wireless bandwidth and the successful deployment of VANETs. We present a Q-Learning-based approach to wirelessly network a big number of vehicles and enable the efficient exchange of data packets among them. More specifically, this work focuses on a IEEE 802.11p-compatible contention-based Medium Access Control (MAC) protocol for efficiently sharing the wireless channel among multiple vehicular stations. The stations feature algorithms that "learn" how to act optimally in a network in order to maximise their achieved packet delivery and minimise bandwidth wastage. Additionally, via a Collective Contention Estimation (CCE) mechanism which we embed on the Q-Learning agent, faster convergence, higher throughput and short-term fairness are achieved