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Tackling the Delay-Cost and Time-Cost Trade-Offs in Computation of Node-Protected Multicast Tree Pairs

机译:在计算受节点保护的组播树对时解决延迟成本和时间成本的折衷方案

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While there are many algorithms for finding a node-protected pair of multicast trees in a graph, all of the existing algorithms suffer from two flaws: Firstly, existing algorithms either have a long running time or produce high-cost tree pairs (Time-Cost Trade-Off). Secondly, existing algorithms aim to produce a low-cost tree pair, but do not take delay constraints into account (Delay-Cost Trade-Off). We tackle these tradeoffs by introducing an iterative algorithm, which finds a low-delay tree pair very quickly and then iteratively seeks lower-cost pairs. We present a sequential version of our algorithm; as well as an architecture for implementing it in a computing cluster, along with the corresponding master-and slave-algorithms.rnIt turns out that the success percentage of our algorithm drops as the average node degree decreases, and as the share of multicast destination nodes increases. Fortunately, in these cases performance of the existing algorithms improves, which means that our algorithm complements the existing algorithms. Two additional benefits or our algorithm are: (1) it can be used in multi-homing scenarios with almost no modifications, and (2) it can be used in both directed and undirected graphs.
机译:虽然有很多算法可以在图中找到一个节点保护的多播树对,但是所有现有算法都存在两个缺陷:首先,现有算法要么运行时间长,要么生成高成本的树对(时间成本交易)。其次,现有算法旨在产生低成本的树对,但不考虑延迟约束(延迟成本权衡)。我们通过引入迭代算法来解决这些折衷,该算法可以很快找到低延迟树对,然后迭代地寻找成本较低的树对。我们介绍了算法的顺序版本;以及相应的主算法和从算法在计算集群中实现的体系结构。结果表明,随着平均节点度的降低以及多播目标节点的份额,我们算法的成功百分比降低增加。幸运的是,在这些情况下,现有算法的性能得以提高,这意味着我们的算法是对现有算法的补充。我们的算法还有两个其他好处:(1)可以在几乎没有任何修改的情况下用于多宿主场景,以及(2)可以用于有向图和无向图。

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