A Resilient Forest-Based Application Level Multicast for Real-Time Streaming

DOI Web Site 参考文献14件
  • TAKAHASHI Kazuya
    Graduate School of Information Science and Technology, Osaka University
  • MORI Tatsuya
    Graduate School of Information Science and Technology, Osaka University
  • HIROTA Yusuke
    Graduate School of Information Science and Technology, Osaka University
  • TODE Hideki
    Graduate School of Engineering, Osaka Prefecture, University
  • MURAKAMI Koso
    Graduate School of Information Science and Technology, Osaka University

抄録

In recent years, real-time streaming has become widespread as a major service on the Internet. However, real-time streaming has a strict playback deadline. Application level multicasts using multiple distribution trees, which are known as forests, are an effective approach for reducing delay and jitter. However, the failure or departure of nodes during forest-based multicast transfer can severely affect the performance of other nodes. Thus, the multimedia data quality is degraded until the distribution trees are repaired. This means that increasing the speed of recovery from isolation is very important, especially in real-time streaming services. In this paper, we propose three methods for resolving this problem. The first method is a random-based proactive method that achieves rapid recovery from isolation and gives efficient “Randomized Forwarding” via cooperation among distribution trees. Each node forwards the data it receives to child nodes in its tree, and then, the node randomly transferring it to other trees with a predetermined probability. The second method is a reactive method, which provides a reliable isolation recovery method with low overheads. In this method, an isolated node requests “Continuous Forwarding” from other nodes if it detects a problem with a parent node. Forwarding to the nearest nodes in the IP network ensures that this method is efficient. The third method is a hybrid method that combines these two methods to achieve further performance improvements. We evaluated the performances of these proposed methods using computer simulations. The simulation results demonstrated that our proposed methods delivered isolation recovery and that the hybrid method was the most suitable for real-time streaming.

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