Toward more localized local algorithms: Removing assumptions concerning global knowledge

Amos Korman, Jean Sébastien Sereni, Laurent Viennot

Research output: Contribution to journalArticlepeer-review


Numerous sophisticated local algorithm were suggested in the literature for various fundamental problems. Notable examples are the MIS and Delta +1-coloring algorithms by Barenboim and Elkin (Distrib Comput 22(5-6):363-379, 2010), by Kuhn (2009), and by Panconesi and Srinivasan (J Algorithms 20(2):356-374, 1996), as well as the 2-coloring algorithm by Linial (J Comput 21:193, 1992). Unfortunately, most known local algorithms (including, in particular, the aforementioned algorithms) are non-uniform, that is, local algorithms generally use good estimations of one or more global parameters of the network, e.g.; the maximum degree Delta; or the number of nodes n. This paper provides a method for transforming a non-uniform local algorithm into a uniform one. Furthermore, the resulting algorithm enjoys the same asymptotic running time as the original non-uniform algorithm. Our method applies to a wide family of both deterministic and randomized algorithms. Specifically, it applies to almost all state of the art non-uniform algorithms for MIS and Maximal Matching, as well as to many results concerning the coloring problem (In particular, it applies to all aforementioned algorithms). To obtain our transformations we introduce a new distributed tool called pruning algorithms, which we believe may be of independent interest.

Original languageEnglish
Pages (from-to)289-308
Number of pages20
JournalDistributed Computing
Issue number5-6
StatePublished - Oct 2013
Externally publishedYes


  • Coloring
  • Distributed algorithm
  • Global knowledge
  • MIS
  • Maximal matching
  • Parameters

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Hardware and Architecture
  • Computer Networks and Communications
  • Computational Theory and Mathematics


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