Non-local probes do not help with many graph problems

Mika Göös, Juho Hirvonen, Reut Levi, Moti Medina, Jukka Suomela

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

Abstract

This work bridges the gap between distributed and centralised models of computing in the context of sublinear-time graph algorithms. A priori, typical centralised models of computing (e.g., parallel decision trees or centralised local algorithms) seem to be much more powerful than distributed message-passing algorithms: centralised algorithms can directly probe any part of the input, while in distributed algorithms nodes can only communicate with their immediate neighbours. We show that for a large class of graph problems, this extra freedom does not help centralised algorithms at all: efficient stateless deterministic centralised local algorithms can be simulated with efficient distributed message-passing algorithms. In particular, this enables us to transfer existing lower bound results from distributed algorithms to centralised local algorithms.

Original languageEnglish
Title of host publicationDistributed Computing - 30th International Symposium, DISC 2016, Proceedings
EditorsCyril Gavoille, David Ilcinkas
PublisherSpringer Verlag
Pages201-214
Number of pages14
ISBN (Print)9783662534250
DOIs
StatePublished - 1 Jan 2016
Externally publishedYes
Event30th International Symposium on Distributed Computing, DISC 2016 - Paris, France
Duration: 27 Sep 201629 Sep 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9888 LNCS

Conference

Conference30th International Symposium on Distributed Computing, DISC 2016
Country/TerritoryFrance
CityParis
Period27/09/1629/09/16

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science

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