In this thesis we deal with the application of Network Coding to guarantee the Quality of Service (QoS) for wireless multi-hop networks. Since the medium is shared, wireless networks suffer from the negative interference impact on the bandwidth. It is thus interesting to propose a Network Coding based approach that takes into account this interference during the routing process. In this context, we first propose an algorithm minimizing the interference impact for unicast flows while respecting their required bandwidth. Then, we combine it with Network Coding to increase the number of admitted flows and with Topology Control to still improve the interference management. We show by simulation the benefit of combining the three fields: Network Coding, interference consideration and Topology Control. We also deal with delay management for multicast flows and use the Generation-Based Network Coding (GBNC) that combines the packets per blocks. Most of the works on GBNC consider a fixed generation size. Because of the network state variations, the delay of decoding and recovering a block of packets can vary accordingly degrading the QoS. To solve this problem, we propose a network-and content-aware method that adjusts the generation size dynamically to respect a certain decoding delay. We also enhance it to overcome the issue of acknowledgement loss. We then propose to apply our approach in a Home Area Network for Live TV and video streaming. Our solution provides QoS and Quality of Experience for the end user with no additional equipment. Finally, we focus on a more theoretical work in which we present a new Butterfly-based network for multi-source multi-destination flows. We characterize the source node buffer size using the queuing theory and show that it matches the simulation results.
Identifer | oai:union.ndltd.org:CCSD/oai:tel.archives-ouvertes.fr:tel-00763375 |
Date | 15 November 2012 |
Creators | Benfattoum, Youghourta, Benfattoum, Youghourta |
Publisher | Université Paris Sud - Paris XI |
Source Sets | CCSD theses-EN-ligne, France |
Language | English |
Detected Language | English |
Type | PhD thesis |
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