Survey on Congestion Detection and Control in Connected Vehicles

The dynamic nature of vehicular ad hoc network (VANET) induced by frequent topology changes and node mobility, imposes critical challenges for vehicular communications. Aggravated by the high volume of information dissemination among vehicles over limited bandwidth, the topological dynamics of VANET causes congestion in the communication channel, which is the primary cause of problems such as message drop, delay, and degraded quality of service. To mitigate these problems, congestion detection, and control techniques are needed to be incorporated in a vehicular network. Congestion control approaches can be either open-loop or closed loop based on pre-congestion or post congestion strategies. We present a general architecture of vehicular communication in urban and highway environment as well as a state-of-the-art survey of recent congestion detection and control techniques. We also identify the drawbacks of existing approaches and classify them according to different hierarchical schemes. Through an extensive literature review, we recommend solution approaches and future directions for handling congestion in vehicular communications

Assessing the Competing Characteristics of Privacy and Safety within Vehicular Ad Hoc Networks

The introduction of Vehicle-to-Vehicle (V2V) communication has the promise of decreasing vehicle collisions, congestion, and emissions. However, this technology places safety and privacy at odds; an increase of safety applications will likely result in the decrease of consumer privacy. The National Highway Traffic Safety Administration (NHTSA) has proposed the Security Credential Management System (SCMS) as the back end infrastructure for maintaining, distributing, and revoking vehicle certificates attached to every Basic Safety Message (BSM). This Public Key Infrastructure (PKI) scheme is designed around the philosophy of maintaining user privacy through the separation of functions to prevent any one subcomponent from identifying users. However, because of the high precision of the data elements within each message this design cannot prevent large scale third-party BSM collection and pseudonym linking resulting in privacy loss. In addition, this philosophy creates an extraordinarily complex and heavily distributed system. In response to this difficulty, this thesis proposes a data ambiguity method to bridge privacy and safety within the context of interconnected vehicles. The objective in doing so is to preserve both Vehicle-to-Vehicle (V2V) safety applications and consumer privacy. A Vehicular Ad-Hoc Network (VANET) metric classification is introduced that explores five fundamental pillars of VANETs. These pillars (Safety, Privacy, Cost, Efficiency, Stability) are applied to four different systems: Non-V2V environment, the aforementioned SCMS, the group-pseudonym based Vehicle Based Security System (VBSS), and VBSS with Dithering (VBSS-D) which includes the data ambiguity method of dithering. By using these evaluation criteria, the advantages and disadvantages of bringing each system to fruition is showcased

Advanced carrier sensing to resolve local channel congestion

Communication performance in VANETs under high channel load is significantly degraded due to packet collisions and messages drops, also referred to as local channel congestion. So far, research was focused on the control of transmit power and the limitation of the messages rate to mitigate the effects of high load. Few attention has been paid to the carrier sensing setup, i.e controlling WHEN the channel is indicated as clear. In previous work, we identified that the Clear Channel Assessment (CCA) as part of the carrier sensing is a very efficient way of controlling the spatial reuse under high load. The CCA threshold determines at which received power level the channel is sensed busy. In this paper, we propose a stepwise CCA Threshold Adjustment (CTA) depending on how long the packet has been waiting already for medium access. This basic and robust approach mitigates significantly the problem of local message queue drops and hence local congestion. The simulation study confirms the reduction of the average and maximum medium access delay as well as the prevention of message queue drops. Even under inaccurate CCA thresholds among the vehicles, fairness in medium access can be maintained by using CTA. In all cases, the awareness of each vehicle is dramatically improved within the safety-critical area of each vehicle

SCALABLE MULTI-HOP DATA DISSEMINATION IN VEHICULAR AD HOC NETWORKS

Vehicular Ad hoc Networks (VANETs) aim at improving road safety and travel comfort, by providing self-organizing environments to disseminate traffic data, without requiring fixed infrastructure or centralized administration. Since traffic data is of public interest and usually benefit a group of users rather than a specific individual, it is more appropriate to rely on broadcasting for data dissemination in VANETs. However, broadcasting under dense networks suffers from high percentage of data redundancy that wastes the limited radio channel bandwidth. Moreover, packet collisions may lead to the broadcast storm problem when large number of vehicles in the same vicinity rebroadcast nearly simultaneously. The broadcast storm problem is still challenging in the context of VANET, due to the rapid changes in the network topology, which are difficult to predict and manage. Existing solutions either do not scale well under high density scenarios, or require extra communication overhead to estimate traffic density, so as to manage data dissemination accordingly. In this dissertation, we specifically aim at providing an efficient solution for the broadcast storm problem in VANETs, in order to support different types of applications. A novel approach is developed to provide scalable broadcast without extra communication overhead, by relying on traffic regime estimation using speed data. We theoretically validate the utilization of speed instead of the density to estimate traffic flow. The results of simulating our approach under different density scenarios show its efficiency in providing scalable multi-hop data dissemination for VANETs

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

Video Streaming over Vehicular Ad Hoc Networks: A Comparative Study and Future Perspectives

Vehicular  Ad Hoc Network  (VANET) is emerged as an important research area that provides ubiquitous short-range connectivity among moving vehicles.  This network enables efficient traffic safety and infotainment applications. One of the promising applications is video transmission in vehicle-to-vehicle or vehicle-to-infrastructure environments.  But, video streaming over vehicular environment is a daunting task due to high movement of vehicles. This paper presents a survey on state-of-arts of video streaming over VANET. Furthermore, taxonomy of vehicular video transmission is highlighted in this paper with special focus on significant applications and their requirements with challenges, video content sharing, multi-source video streaming and video broadcast services. The comparative study of the paper compares the video streaming schemes based on type of error resilient technique, objective of study, summary of their study, the utilized simulator and the type of video sharing.  Lastly, we discussed the open issues and research directions related to video communication over VANET

Achieving dynamic road traffic management by distributed risk estimation in vehicular networks

In this thesis I develop a model for a dynamic and fine-grained approach to traffic management based around the concept of a risk limit: an acceptable or allowable level of accident risk which vehicles must not exceed. Using a vehicular network to exchange risk data, vehicles calculate their current level of accident risk and determine their behaviour in a distributed fashion in order to meet this limit. I conduct experimental investigations to determine the effectiveness of this model, showing that it is possible to achieve gains in road system utility in terms of average vehicle speed and overall throughput whilst maintaining the accident rate. I also extend this model to include risk-aware link choice and social link choice, in which vehicles make routing decisions based on both their own utility and the utility of following vehicles. I develop a coupled risk estimation algorithm in which vehicles use not only their own risk calculations but also estimates received from neighbouring vehicles in order to arrive at a final risk value. I then analyse the performance of this algorithm in terms of its convergence rate and bandwidth usage and examine how to manage the particular characteristics of a vehicular ad-hoc network, such as its dynamic topology and high node mobility. I then implement a variable-rate beaconing scheme to provide a trade-off between risk estimate error and network resource usage