Round-and message-optimal distributed graph algorithms
Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing, 2018•dl.acm.org
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 …
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 …
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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