Distributed Computing with Advice: Information Sensitivity of Graph Coloring

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.

• Type: Conference
• Year: 2007
• Where: ICALP
• Authors: Pierre Fraigniaud, Cyril Gavoille, David Ilcinkas, Andrzej Pelc
• Keywords: Fast Distributed Computations, ICALP 2007, Information, Information Sensitivity, Programming Languages