Fast and proximity-aware multi-source overlay multicast under heterogeneous environment

  • Authors:
  • Zhenyu Li;Zengyang Zhu;Gaogang Xie;Zhongcheng Li

  • Affiliations:
  • Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, PR China and Graduate School of Chinese Academy of Sciences, Beijing 100049, PR China;Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, PR China and Graduate School of Chinese Academy of Sciences, Beijing 100049, PR China;Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, PR China;Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, PR China

  • Venue:
  • Computer Communications
  • Year:
  • 2009

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Abstract

Overlay multicast has been considered as one of the most important developments for the next generation Internet infrastructure. In this paper, we consider overlay multicast in the scenarios where any participant node is a potential data source. Existing multicast algorithms for single-source always require a long time to deliver messages or have high maintenance overhead when multiple data sources are allowed. There are other algorithms that are designed for multi-source scenarios. But they consume too much network resources and have a long convergence time because of proximity ignorance. To address the issues, we present FPCast, which leverages node heterogeneity and proximity information at the same time. Physically close nodes are grouped into clusters and each cluster selects a powerful, stable node as its rendezvous point. The rendezvous nodes form a DHT-based structure. Data messages are replicated and forwarded along implicit, source specific, and heterogeneity-aware multicast trees. We further reduce the delivery delay by introducing probabilistic forwarding scheme. We show the average delivery path length converges to O(logn) automatically (n is the number of nodes in the overlay). The simulation results demonstrate the superiority of our algorithm in terms of message delivery time and network resource consumption, in comparison with the previous randomized algorithms. The algorithm is also resilient to node failures.