Distributed Symmetry Breaking on Power Graphs via Sparsification

Yannic Maus, Saku Peltonen, Jara Uitto

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

2 Citations (Scopus)
57 Downloads (Pure)

Abstract

In this paper we present efficient distributed algorithms for classical symmetry breaking problems, maximal independent sets (MIS) and ruling sets, in power graphs. We work in the standard CONGEST model of distributed message passing, where the communication network is abstracted as a graph G. Typically, the problem instance in CONGEST is identical to the communication network G, that is, we perform the symmetry breaking in G. In this work, we consider a setting where the problem instance corresponds to a power graph Gk, where each node of the communication network G is connected to all of its k-hop neighbors.A β-ruling set is a set of non-adjacent nodes such that each node in G has a ruling neighbor within β hops; a natural generalization of an MIS. On top of being a natural family of problems, ruling sets (in power graphs) are well-motivated through their applications in the powerful shattering framework [BEPS JACM'16, Ghaffari SODA'19] (and others). We present randomized algorithms for computing maximal independent sets and ruling sets of Gk in essentially the same time as they can be computed in G. Our main contribution is a deterministic poly(k, log n) time algorithm for computing k-ruling sets of Gk, which (for k > 1) improves exponentially on the current state-of-the-art runtimes. Our main technical ingredient for this result is a deterministic sparsification procedure which may be of independent interest.We also revisit the shattering algorithm for MIS [BEPS J'ACM'16] and present different approaches for the post-shattering phase. Our solutions are algorithmically and analytically simpler (also in the LOCAL model) than existing solutions and obtain the same runtime as [Ghaffari SODA'16].

Original languageEnglish
Title of host publicationPODC 2023 - Proceedings of the 2023 ACM Symposium on Principles of Distributed Computing
PublisherACM
Pages157-167
Number of pages11
ISBN (Electronic)979-8-4007-0121-4
DOIs
Publication statusPublished - 19 Jun 2023
MoE publication typeA4 Conference publication
EventACM Symposium on Principles of Distributed Computing - Orlando, United States
Duration: 19 Jun 202323 Jun 2023

Conference

ConferenceACM Symposium on Principles of Distributed Computing
Abbreviated titlePODC
Country/TerritoryUnited States
CityOrlando
Period19/06/202323/06/2023

Keywords

  • CONGEST model
  • distributed algorithm
  • maximal independent set
  • power graphs
  • ruling sets
  • shattering
  • sparsification

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