Brief Announcement: Computing Power of Hybrid Models in Synchronous Networks

Pierre Fraigniaud, Pedro Montealegre, Pablo Paredes, Ivan Rapaport, Martín Ríos-Wilson, Ioan Todinca

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

Abstract

During the last two decades, a small set of distributed computing models for networks have emerged, among which LOCAL, CONGEST, and Broadcast Congested Clique (BCC) play a prominent role. We consider hybrid models resulting from combining these three models. That is, we analyze the computing power of models allowing to, say, perform a constant number of rounds of CONGEST, then a constant number of rounds of LOCAL, then a constant number of rounds of BCC, possibly repeating this figure a constant number of times. We specifically focus on 2-round models, and we establish the complete picture of the relative powers of these models. That is, for every pair of such models, we determine whether one is (strictly) stronger than the other, or whether the two models are incomparable.

Original languageEnglish
Title of host publication36th International Symposium on Distributed Computing, DISC 2022
EditorsChristian Scheideler
PublisherSchloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing
ISBN (Electronic)9783959772556
DOIs
StatePublished - 1 Oct 2022
Externally publishedYes
Event36th International Symposium on Distributed Computing, DISC 2022 - Augusta, United States
Duration: 25 Oct 202227 Oct 2022

Publication series

NameLeibniz International Proceedings in Informatics, LIPIcs
Volume246
ISSN (Print)1868-8969

Conference

Conference36th International Symposium on Distributed Computing, DISC 2022
Country/TerritoryUnited States
CityAugusta
Period25/10/2227/10/22

Keywords

  • Broadcast Congested Clique
  • CONGEST
  • LOCAL
  • hybrid model
  • synchronous networks

Fingerprint

Dive into the research topics of 'Brief Announcement: Computing Power of Hybrid Models in Synchronous Networks'. Together they form a unique fingerprint.

Cite this