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A fast distributed approximation algorithm for minimum spanning trees

机译:最小生成树的快速分布式近似算法

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Abstract We present a distributed algorithm that constructs an O (log n)-approximate minimum spanning tree (MST) in any arbitrary network. This algorithm runs in time O (D (G)+ L(G, ω)) where L(G, ω) is a parameter called the local shortest path diameter and D{G) is the (unweighted) diameter of the graph. Our algorithm is existentially optimal (up to polylogarithmic factors), i.e., there exist graphs which need Q(D(G) + L(G, ω)) time to compute an H-approximation to the MST for any H ∈ [1, Θ(log n)]. Our result also shows that there can be a significant time gap between exact and approximate MST computation: there exists graphs in which the running time of our approximation algorithm is exponentially faster than the time-optimal distributed algorithm that computes the MST. Finally, we show that our algorithm can be used to find an approximate MST in wireless networks and in random weighted networks in almost optimal O(D(G)) time.
机译:摘要我们提出了一种分布式算法,该算法可在任意网络中构造O(log n)近似最小生成树(MST)。该算法在时间O(D(G)+ L(G,ω))上运行,其中L(G,ω)是称为局部最短路径直径的参数,D {G)是图的(未加权)直径。我们的算法是存在最优的(取决于多对数因子),即对于任何H∈[1,存在需要Q(D(G)+ L(G,ω))时间来计算MST的H近似的图。 Θ(log n)]。我们的结果还表明,精确的MST和近似的MST计算之间可能存在较大的时间间隔:存在一些图表,其中逼近算法的运行时间比计算MST的时间最优分布式算法的指数速度快。最后,我们证明了我们的算法可用于在几乎最佳的O(D(G))时间内在无线网络和随机加权网络中找到近似的MST。

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