Distributed approximate k-core decomposition and min-max edge orientation: Breaking the diameter barrier

T. H. Hubert Chan, Mauro Sozio, Bintao Sun

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

Abstract

We design distributed algorithms to compute approximate solutions for several related graph optimization problems. All our algorithms have round complexity being logarithmic in the number of nodes of the underlying graph and in particular independent of the graph diameter. By using a primal-dual approach, we develop a 2(1 + ε)-approximation algorithm for computing the coreness values of the nodes in the underlying graph, as well as a 2(1 + ε)-approximation algorithm for the min-max edge orientation problem, where the goal is to orient the edges so as to minimize the maximum weighted in-degree. We provide lower bounds showing that the aforementioned algorithms are tight both in terms of the approximation guarantee and the round complexity. Finally, motivated by the fact that the densest subset problem has an inherent dependency on the diameter of the graph, we study a weaker version that does not suffer from the same limitation.

Original languageEnglish
Title of host publicationProceedings - 2019 IEEE 33rd International Parallel and Distributed Processing Symposium, IPDPS 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages345-354
Number of pages10
ISBN (Electronic)9781728112466
DOIs
Publication statusPublished - 1 May 2019
Externally publishedYes
Event33rd IEEE International Parallel and Distributed Processing Symposium, IPDPS 2019 - Rio de Janeiro, Brazil
Duration: 20 May 201924 May 2019

Publication series

NameProceedings - 2019 IEEE 33rd International Parallel and Distributed Processing Symposium, IPDPS 2019

Conference

Conference33rd IEEE International Parallel and Distributed Processing Symposium, IPDPS 2019
Country/TerritoryBrazil
CityRio de Janeiro
Period20/05/1924/05/19

Keywords

  • Coreness
  • Distributed algorithms
  • Round complexity

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