一种定位优先的可扩展覆盖组播方法

M. Kâafar, T. Turletti, W. Dabbous
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引用次数: 3

摘要

最近关于组播覆盖结构的一些建议已经证明了利用底层网络拓扑结构的重要性。然而,这些拓扑感知的建议通常依赖于增量和周期性的改进来提高系统性能。因此,这些方法既不具有可扩展性,因为它们由于改进开销而导致通信成本高,也不高效,因为获得稳定的结构需要很长的收敛时间。在本文中,我们提出了一种高度可扩展的定位算法,该算法可以在不产生高开销的情况下逐渐将新来者引导到他们最近的一组节点。在此定位过程的基础上,我们构建了一个鲁棒且可扩展的拓扑感知聚类分层覆盖方案,称为LCC。我们通过仿真和PlanetLab实验来评估LCC的性能。结果表明,定位过程在时间和带宽方面需要适度的资源。此外,LCC在支持大规模组播应用方面表现出良好的性能
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Locating-First Approach for Scalable Overlay Multicast
Recent proposals in multicast overlay construction have demonstrated the importance of exploiting underlying network topology. However, these topology-aware proposals often rely on incremental and periodic refinements to improve the system performance. These approaches are therefore neither scalable, as they induce high communication cost due to refinement overhead, nor efficient because long convergence time is necessary to obtain a stabilized structure. In this paper, we propose a highly scalable locating algorithm that gradually directs newcomers to their a set of their closest nodes without inducing high overhead. On the basis of this locating process, we build a robust and scalable topology-aware clustered hierarchical overlay scheme, called LCC. We conducted both simulations and PlanetLab experiments to evaluate the performance of LCC. Results show that the locating process entails modest resources in terms of time and bandwidth. Moreover, LCC demonstrates promising performance to support large scale multicast applications
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