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Dynamic on-line group-tree matching for large scale group communications: a performance study

机译:用于大规模组通信的动态在线组匹配:绩效研究

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Traditional IP multicast faces a serious state scalability problem when there are a large number of groups in the network. Recently, a novel approach called aggregated multicast was proposed [6], in which multiple groups share one delivery tree. A key problem in aggregated multicast is group-tree matching (i.e., assigning groups to trees). In this paper, we formally study the dynamic version of the group-tree matching problem. We propose a generic dynamic on-line algorithm (GDOA) and provide an approach to determine the upper bound on its performance. We quantitatively compare the performance of GDOA and other existing on-line heuristics. Extensive simulations demonstrate that GDOA is a very practical solution with promising performance and reasonable computation requirement.
机译:当网络中有大量组时,传统的IP多播面临严重的状态可扩展性问题。最近,提出了一种称为聚合多播的新方法[6],其中多个组共享一个递送树。聚合多播中的一个关键问题是组树匹配(即,将组分配给树)。在本文中,我们正式研究了组树匹配问题的动态版本。我们提出了一种通用的动态在线算法(GDOA),并提供了一种确定其性能上限的方法。我们量化地比较GDOA和其他现有的在线启发式的性能。广泛的模拟表明,GDOA是一种非常实用的解决方案,具有良好的性能和合理的计算要求。

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