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A distributed graph algorithm for the detection of local cycles and knots

机译:用于检测局部周期和节的分布式图算法

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In this paper, a distributed cycle/knot detection algorithm for general graphs is presented. The algorithm distinguishes between cycles and knots and is the first algorithm to our knowledge which does so. It is especially relevant to an application such as parallel simulation in which 1) cycles and knots can arise frequently 2) the size of the graph is very large, and 3) it is necessary to know if a given node is in a cycle or a knot. It requires less communication than previous algorithms-2m vs. (at least) (4m) for the Chandy and Misra algorithm, where m is the number of links in the graph. It requires O (nlog (n)) bits of memory, where n is the number of nodes. The algorithm differs from the classical diffusing computation methods through its use of incomplete search messages to speed up the computation. We introduce a marking scheme in order to identify strongly connected subcomponents of the graph which cannot reach the initiator of the algorithm. This allows us to distinguish between the case in which the initiator is in a cycle (only) or is in a knot.
机译:本文提出了一种通用图的分布式周期/结检测算法。该算法可区分循环和节,是我们所知的第一个实现此功能的算法。它与并行仿真之类的应用特别相关,在这种应用中,1)周期和结可能频繁出现; 2)图的大小非常大; 3)有必要知道给定节点是处于周期还是处于循环状态。结。与以前的算法相比,它所需的通信更少-2m,而对于Chandy和Misra算法而言,(至少)为(4m),其中m是图中的链接数。它需要O(nlog(n))位内存,其中n是节点数。该算法与经典的扩散计算方法不同,它使用不完整的搜索消息来加快计算速度。我们引入一种标记方案,以识别图的强连接子组件,这些子组件无法到达算法的发起者。这使我们可以区分发起者是循环(仅)还是打结。

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