圆形和消息最优分布式图算法

Bernhard Haeupler, D. E. Hershkowitz, David Wajc
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引用次数: 42

摘要

分布式图算法对所使用的轮数或发送的消息总数分别进行优化,已经得到了广泛的研究。然而,对这两种措施同时有效的算法一直难以捉摸。例如,直到最近才表明,对于最小生成树(MST),通过通信的CONGEST模型中的单个算法可以实现最佳消息和轮复杂度(最多可达多对数项)。在本文中,我们提供了一些同时是圆和消息最优的算法,用于许多研究得很好的分布式优化问题。我们的主要成果是这样一种分布式算法,用于在图分区的每个部分上计算简单函数的基本原语。从该算法中,我们导出了多个问题的圆形和消息最优算法,包括MST,近似最小切割和近似单源最短路径等。在一般图上,我们所有的算法都实现了最坏情况下的最优Õ (D+√n)轮复杂度和Õ (m)消息复杂度。此外,我们的算法需要平面、属界、树宽度有界和路径宽度有界图上的最优Õ (D)轮和Õ (n)个消息。
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Round- and Message-Optimal Distributed Graph Algorithms
Distributed graph algorithms that separately optimize for either the number of rounds used or the total number of messages sent have been studied extensively. However, algorithms simultaneously efficient with respect to both measures have been elusive. For example, only very recently was it shown that for Minimum Spanning Tree (MST), an optimal message and round complexity is achievable (up to polylog terms) by a single algorithm in the CONGEST model of communication. In this paper we provide algorithms that are simultaneously round- and message-optimal for a number of well-studied distributed optimization problems. Our main result is such a distributed algorithm for the fundamental primitive of computing simple functions over each part of a graph partition. From this algorithm we derive round- and message-optimal algorithms for multiple problems, including MST, Approximate Min-Cut and Approximate Single Source Shortest Paths, among others. On general graphs all of our algorithms achieve worst-case optimal Õ (D+√ n) round complexity and Õ (m) message complexity. Furthermore, our algorithms require an optimal Õ (D) rounds and Õ (n) messages on planar, genus-bounded, treewidth-bounded and pathwidth-bounded graphs.
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