Network coding-based approach for efficient video streaming over MANET

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• 作者：Olfa Ben Rhaiem ; ^a ; ^{olfa.benrhaiem@gmail.com" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Lamia Chaari Fourati^a ; ^{lamia.chaari@enis.rnu.tn" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Wessam Ajib^b ; ^{ajib.wessam@uqam.ca" class="auth_mail" title="E-mail the corresponding author}Author Vitae
• 关键词：Video streaming ; Cross-layer ; MANET ; Multicast ; Network coding
• 刊名：Computer Networks
• 出版年：2016
• 出版时间：5 July 2016
• 年：2016
• 卷：103
• 期：Complete
• 页码：84-100
• 全文大小：2670 K

文摘

Video streaming over mobile ad-hoc networks is becoming a highly important application for reliably delivering the content between the user and the content storage node. The key challenge is, hence, to address the impact of the user mobility on the quality of the delivered video. Accordingly, the pioneering concept of network coding (NC) emerges as a promising approach for improving the video transmission quality mainly in multicast mobile environment. This work focuses on improving the Quality of Service of video streaming over mobile ad-hoc networks using random NC. We consider video coded by the widely-used H264/SVC codec that generates packets with different priorities and provides traffic differentiation using the IEEE 802.11e MAC. Intuitively, focusing on lowering the error transmission of high priority packets leads to enhance the video streaming quality. Accordingly, this work develops and proposes a new scalable transmission scheme that decreases the loss of high priority packets. Our approach, named Extended Multicast Scalable Video Transmission using Classification-Scheduling Algorithms and Network Coding over MANET (and denoted EMSCNC), adopts a cross layer design between the H.264/SVC codec, the network and MAC layers. Moreover, we develop an analytical framework allowing the performance evaluation in terms of throughput, delay, and packet delivery ratio. Simulation results validate our analytical model and confirm the substantial performance improvement brought by our approach.