Improved approximation guarantees for weighted matching in the semi-streaming model

Leah Epstein, Asaf Levin, Julián Mestre, Danny Segev

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

Abstract

We study the maximum weight matching problem in the semi-streaming model, and improve on the currently best one-pass algorithm due to Zelke (Proc. STACS '08, pages 669-680) by devising a deterministic approach whose performance guarantee is 4.91 + ε. In addition, we study preemptive online algorithms, a sub-class of one-pass algorithms where we are only allowed to maintain a feasible matching in memory at any point in time. All known results prior to Zelke's belong to this sub-class. We provide a lower bound of 4.967 on the competitive ratio of any such deterministic algorithm, and hence show that future improvements will have to store in memory a set of edges which is not necessarily a feasible matching. We conclude by presenting an empirical study, conducted in order to compare the practical performance of our approach to that of previously suggested algorithms.

Original languageEnglish
Title of host publicationSTACS 2010 - 27th International Symposium on Theoretical Aspects of Computer Science
Pages347-358
Number of pages12
DOIs
StatePublished - 2010
Externally publishedYes
Event27th International Symposium on Theoretical Aspects of Computer Science, STACS 2010 - Nancy, France
Duration: 4 Mar 20106 Mar 2010

Publication series

NameLeibniz International Proceedings in Informatics, LIPIcs
Volume5
ISSN (Print)1868-8969

Conference

Conference27th International Symposium on Theoretical Aspects of Computer Science, STACS 2010
Country/TerritoryFrance
CityNancy
Period4/03/106/03/10

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