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Title: Analysis and design of efficient medium access control schemes for vehicular ad-hoc networks
Author: Han, Chong
ISNI:       0000 0004 2742 2537
Awarding Body: University of Surrey
Current Institution: University of Surrey
Date of Award: 2012
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In this dissertation, analysis and design of the efficient Medium Access Control (MAC) sub-layer schemes are considered for Vehicular Ad hoc Networks (VANETs). The contributions of this study are three-fold. First, an analytical model based on Markov chain is developed in order to investigate the performance of the MAC sub-layer of the IEEE 802. 11p for vehicular communications. The results indicate that single channel MAC sub-layers may not be adequate for the future Intelligent Transportation Systems (ITS). The analytical model is validated with the results from simulation-based analysis. Performance analysis based on simulations is given on MAC metrics such as throughput, access delay, packet delivery. Second, a multi-channel MAC protocol is proposed and comprehensively analyzed in terms of channel utilizing and Quality of service (QoS) differentiation for dense VANETs. It is demonstrated that the proposed scheme, namely Asynchronous Multichannel MAC with Distributed TDM A (AMCMAC-D), improves the system performance in terms of throughput, packet delivery rate, collision rate on service channels, load balancing, and service differentiation for dense vehicular networks. Third, to cope with the interference from contention with neighbours within two hops in large-scale networks, a Large-scale Asynchronous Multichannel MAC (LS-AMCMAC) is proposed. The proposed scheme outperforms other benchmark multichannel MAC schemes in large-scale networks, in terms of throughput, channel utilization, dissemination of emergency messages, and the collision rates on control and service channels.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: VANET, Random Access MAC, Multichannel MAC