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Distributed Computing with Advice: Information Sensitivity of Graph Coloring

  • Pierre Fraigniaud
  • Cyril Gavoille
  • David Ilcinkas
  • Andrzej Pelc
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4596)

Abstract

We study the problem of the amount of information (advice) about a graph that must be given to its nodes in order to achieve fast distributed computations. The required size of the advice enables to measure the information sensitivity of a network problem. A problem is information sensitive if little advice is enough to solve the problem rapidly (i.e., much faster than in the absence of any advice), whereas it is information insensitive if it requires giving a lot of information to the nodes in order to ensure fast computation of the solution. In this paper, we study the information sensitivity of distributed graph coloring.

Keywords

Chromatic Number Information Sensitivity Graph Coloring Impossibility Result Oriented Cycle 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Pierre Fraigniaud
    • 1
  • Cyril Gavoille
    • 2
  • David Ilcinkas
    • 3
  • Andrzej Pelc
    • 3
  1. 1.CNRS and University Paris 7 
  2. 2.LaBRI, Université Bordeaux 1 
  3. 3.Département d’informatique, Université du Québec en Outaouais 

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