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A Load-Balanced Video Multicast Routing System in Software-Defined Networks
Thesis

A Load-Balanced Video Multicast Routing System in Software-Defined Networks

Lee, Meng-Wei
Masters, 國立清華大學, 資訊工程學系
2015

Abstract

軟體定義網路 群播路由 影音群播 Sudan Software-Defined Network Multicast routing Video multicast
IP multicast in traditional networks, dictates high-end routers and incurs high administrative overhead, which is no longer suitable for deployment due to its complicated operations. In this thesis, we implement a multicast routing system based on SDN framework. For computing the multicast routes, we study the problem of establishing multipath multicast routing for streaming videos in Software-Defined Networks (SDNs). The objectives of the considered problem are robustness, load balance, adaptiveness, and SDN compatibility. We formulate the multicast routing problem into a mathematical optimization problem and propose a min-max link load multicast routing algorithm, called Robust Multipath Multicast Routing (RMMR∗). We further design a heuristic algorithm to obtain the multicast trees efficiently. We implement our proposed algorithm in our multicast routing system on OpenFlow controller. We conduct the experiments in real testbed and Mininet emulator to demonstrate the practicality, performance and scalability. In the experiment of real testbed, we measure the response time of our system: (i) all operations of flow-entries insertion are completed in less than 5 milliseconds, (ii) the detection time of all clients are no more than 0.15 second. The results of experiment in emulator show the merits of our algorithms over the IP multicast, e.g., we observe: (i) frame loss rate reduction between 19% and 95%, (ii) video quality improvement between 4 dB and 15 dB, (iii) sink throughput increase between 25% and 66%, and (iv) maximal link utilization reduction between 15% and 50%. We also show the tradeoff between optimality and run time of the two proposed algorithms: one of them is more suitable for smaller and more static networks, and the other one is more suitable for larger and more dynamic networks.

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