Best of two local models: Centralized local and distributed local algorithms

Guy Even, Moti Medina, Dana Ron

Research output: Contribution to journalArticlepeer-review

9 Scopus citations


We consider two models of computation: centralized local algorithms and local distributed algorithms. Algorithms in one model are adapted to the other model to obtain improved algorithms. Distributed vertex coloring is employed to design improved centralized local algorithms for: maximal independent set, maximal matching, and an approximation scheme for maximum (weighted) matching over bounded degree graphs. The improvement is threefold: the algorithms are deterministic, stateless, and the number of probes grows polynomially in log⁡n, where n is the number of vertices of the input graph. The recursive centralized local improvement technique by Nguyen and Onak (FOCS 2008) is employed to obtain a distributed approximation scheme for maximum (weighted) matching.

Original languageEnglish
Pages (from-to)69-89
Number of pages21
JournalInformation and Computation
StatePublished - Oct 2018
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2018 Elsevier Inc.


Research supported by the Israel Science Foundation grant number 671/13.

FundersFunder number
Israel Science Foundation671/13


    • Centralized local algorithms
    • Distributed local algorithms
    • Graph algorithms
    • Maximum matching
    • Maximum weighted matching
    • Sublinear approximation algorithms


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