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Flow Decompositions in External Memory

机译:外部存储器中的流分解

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Let G = (V, E) be a digraph with disjoint sets of sources S (C) V and sinks T (C) V endowed with an S-T flow f : E → Z_+. It is a well-known fact that f decomposes into a sum ∑_(st)f_(st) of s-t flows f_(st) between all pairs of sources s ∈ S and sinks t ∈ T. In the usual RAM model, such a decomposition can be found in O(E log V~2/E) time. The present paper concerns the complexity of this problem in the external memory model (introduced by Aggarwal and Vitter). The internal memory algorithm involves random memory access and thus becomes inefficient. We propose two novel methods. The first one requires O(Sort(E) log V~2/E) I/Os and the second one takes O(Sort(E) log U) expected I/Os (where U denotes the maximum value of f).
机译:令G =(V,E)为有向图,其中源S(C)V为不相交集,而汇聚的T(C)V为S-T流f:E→Z_ +。一个众所周知的事实是,f分解为所有源对s∈S与下沉t∈T之间的st流f_(st)的st流f_(st)的总和。分解时间为O(E log V〜2 / E)。本文涉及外部存储模型中此问题的复杂性(由Aggarwal和Vitter引入)。内部存储器算法涉及随机存储器访问,因此效率低下。我们提出了两种新颖的方法。第一个需要O(Sort(E)log V〜2 / E)I / O,第二个需要O(Sort(E)log U)个期望的I / O(其中U表示f的最大值)。

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