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Sofiane Zemouri, "Enhanced Wireless Congestion Control in Urban Vehicular Environments," PhD Thesis, School of Computer Science, University College Dublin, July 2016. (Advisors: John Murphy and Soufiene Djahel; Referees: Falko Dressler and Declan Delaney)


Despite many recent advances in the field of Vehicular Ad Hoc Networks (VANETs), channel congestion remains one of the main challenges facing the VANET research community. Considerable efforts have been directed in recent years towards designing flexible yet robust solutions to control channel load in VANETs, such as the ETSI initiative DCC (Decentralised Congestion Control). Despite these efforts, without a deep understanding of the mechanics that govern this load, its management and processing is still an open issue. This thesis provides a comprehensive study of the wireless channel capacity in VANETs and sets an approximation for its upper limit in order to study the mechanics of congestion control. Different possible ways of achieving this control are investigated through analysing the spatial dimension (geographic region), in terms of messaging requirements, as well as the temporal dimension (periodicity and messaging frequency). Then a discussion of the best combination that leverages the strengths of both congestion control approaches is given. In order to control the load generated by multi-hop event-driven warning messages, a distributed dissemination protocol for safety information in urban areas, Road-Casting Protocol (RCP), is introduced. RCP is based on a novel cooperative forwarding mechanism that reduces the number of messages disseminated while reaching the maximum number of targeted vehicles. Moreover, an accurate definition of the Region of Interest (RoI) - namely, the geographical scope - of each broadcasted safety message is determined in order to minimize the impact of these messages on the channel load and limit it to the targeted area. Furthermore, in order to control the load generated by single-hop periodic beacon messages, a new congestion control protocol, the Prediction and Adaptation Algorithm (P&A-A), is presented that performs a joint adaptation of the transmit rate and power. P&A-A relies on a short-term vehicular density prediction algorithm to forecast peaks in the channel load and proactively take the required measures in order to avoid message collisions. Additionally, P&A-A adapts the transmit parameters to guarantee the required operation of the most critical VANET applications.

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Sofiane Zemouri

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    author = {Zemouri, Sofiane},
    title = {{Enhanced Wireless Congestion Control in Urban Vehicular Environments}},
    advisor = {Murphy, John and Djahel, Soufiene},
    institution = {School of Computer Science},
    location = {Dublin, Ireland},
    month = {7},
    referee = {Dressler, Falko and Delaney, Declan},
    school = {University College Dublin},
    type = {PhD Thesis},
    year = {2016},

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