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Approximation and heuristic algorithms for minimum delay application-layer multicast trees

机译:最小延迟应用层多播树的近似和启发式算法

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We investigate the problem of finding the minimum delay application-layer multicast trees, such as the trees constructed in overlay networks. It is accepted that shortest path trees are not a good solution for the problem since such trees can have nodes with very large degree, termed high load nodes. The load on these nodes makes them a bottleneck in the distribution tree, due to computation load and access link bandwidth constrains. Many previous solutions limited the maximal degree of the nodes by introducing arbitrary constraints. In this work, we show how to directly map the node load to the delay penalty at the application host, and create a new model that captures the trade offs between the desire to select shortest path trees and the need to constrain the load on the hosts. In this model the problem is shown to be NP-hard. Therefore, we present a logarithmic approximation algorithm and an alternative heuristic solution. Our heuristic algorithm is shown by simulations to be scalable for large group sizes, and produces results that are very close to optimal.
机译:我们调查寻找最小延迟的应用层多播树(例如在覆盖网络中构建的树)的问题。公认的是,最短路径树不是解决该问题的好方法,因为此类树可能具有程度非常高的节点,称为高负载节点。由于计算负载和访问链路带宽的限制,这些节点上的负载使它们成为分发树中的瓶颈。许多先前的解决方案通过引入任意约束来限制节点的最大程度。在这项工作中,我们展示了如何将节点负载直接映射到应用程序主机上的延迟损失,并创建一个新模型来捕获在选择最短路径树的需求与约束主机上负载之间的权衡取舍。 。在此模型中,问题显示为NP难的。因此,我们提出了一种对数逼近算法和一种替代的启发式解决方案。通过仿真显示,我们的启发式算法可针对大型团体扩展,并产生非常接近最佳结果的结果。

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