基于网络编码的多源分层组播吞吐量优化算法研究

Research on Optimization Algorithm of Layered Multicast Throughput with Multiple Source Media Based on Network Coding

分层组播是现实网络环境中流媒体分发的必要手段,在分层组播中应用网络编码可以进一步提高组播的吞吐量。但是,已有的基于网络编码的分层组播机制仅仅考虑了单个媒体源的情形,对于网络中同时存在多个媒体源的场景则缺乏研究。采用遗传算法解决网络编码条件下的多源分层组播的吞吐量优化问题,通过把握源间和层间编码机会,有效提高了网络带宽利用率。仿真实验表明,与传统的分层组播策略相比,文章所提出的优化算法可以有效提高多源分层组播的吞吐量。

Layered muhicast is the necessary way to distribute streaming media in real network environment, and using network coding in layered muhicast can further improve muhieast throughput. However, existing layered muhicast methods based on network coding have only considered single source media and are lack of research on multiple source meidia. This paper solves optimization problems of layered muhieast throughput with multiple source media using genetic algorithm based on network coding. The application of different source media coding and different layer coding can improve bandwidth utilization more efficiently. Simulation results illustrate that the optimization algorithm of layered multieast throughput with multiple source media proposed in this paper is superior to traditional layered multicast methods.