Single-Source Shortest Paths in the CONGEST Model with Improved Bound

Shiri Chechik, Doron Mukhtar

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We improve the time complexity of the single-source shortest path problem for weighted directed graphs (with non-negative integer weights) in the Broadcast CONGEST model of distributed computing. For polynomially bounded edge weights, the state-of-the-art algorithm for this problem requires [EQUATION] rounds [Forster and Nanongkai, FOCS 2018], which is quite far from the known lower bound of [EQUATION] rounds [Elkin, STOC 2014]; here D is the diameter of the underlying network and n is the number of vertices in it. For the approximate version of this problem, Forster and Nanongkai [FOCS 2018] obtained an upper bound of [EQUATION], and stated that achieving the same bound for the exact case remains a major open problem. In this paper we resolve the above mentioned problem by devising a new randomized algorithm for solving (the exact version of) this problem in [EQUATION] rounds. Our algorithm is based on a novel weight-modifying technique that allows us to compute bounded-hop distance approximation that preserves a certain form of the triangle inequality for the edges in the graph.

Original languageEnglish
Title of host publicationPODC 2020 - Proceedings of the 39th Symposium on Principles of Distributed Computing
PublisherAssociation for Computing Machinery
Pages464-473
Number of pages10
ISBN (Electronic)9781450375825
DOIs
StatePublished - 31 Jul 2020
Event39th Symposium on Principles of Distributed Computing, PODC 2020 - Virtual, Online, Italy
Duration: 3 Aug 20207 Aug 2020

Publication series

NameProceedings of the Annual ACM Symposium on Principles of Distributed Computing

Conference

Conference39th Symposium on Principles of Distributed Computing, PODC 2020
Country/TerritoryItaly
CityVirtual, Online
Period3/08/207/08/20

Keywords

  • broadcast CONGEST
  • distributed algorithms
  • overlay networks
  • single-source shortest paths

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