Advertisement

An Experimental Assessment of a Stochastic, Anytime, Decentralized, Soft Colourer for Sparse Graphs

  • Stephen Fitzpatrick
  • Lambert Meertens
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2264)

Abstract

This paper reports on a simple, decentralized, anytime, stochastic, soft graph-colouring algorithm. The algorithm is designed to quickly reduce the number of colour conflicts in large, sparse graphs in a scalable, robust, low-cost manner. The algorithm is experimentally evaluated in a framework motivated by its application to resource coordination in large, distributed networks.

Keywords

Constraint optimization conflict minimization decentralized algorithms anytime algorithms graph colouring 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 2.
    Iterated Greedy Graph Colouring and the Difficulty Landscape,Joseph Culberson, Technical Report TR 92-07, Department of Computing Science, The University of Alberta, Edmonton, Alberta, Canada, June 1992Google Scholar
  2. 3.
    Parallel Distributed Constraint Satisfaction, Marko Fabiunke, Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA’99), pp 1585–1591, Las Vegas, June 1999Google Scholar
  3. 4.
    An Incomplete Method for Solving Distributed Valued Constraint Satisfaction Problems, Michel Lemaitre & Gerard Verfaillie, AAAI-97, Workshopon Constraints and Agents, Providence, Rhode Island, USA, July 1997Google Scholar
  4. 5.
    Experiments with Parallel Graph Colouring Heuristics, Gary Lewandowski & Anne Condon, in Cliques, Colouring and Satisfiability, DIMACS Series in Discrete Mathematics and Theoretical Computer Science, Volume 26, American Mathematical Society, 1996, pages 309–334Google Scholar
  5. 6.
    The Distributed Constraint Satisfaction Problem: Formalization and Algorithms, Makoto Yokoo, Edmund H. Durfee, Toru Ishida & Kazuhiro Kuwabara, IEEE trans. on Knowledge and Data Engineering, vol. 10, no. 5, September/October 1998Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Stephen Fitzpatrick
    • 1
  • Lambert Meertens
    • 1
  1. 1.Kestrel InstitutePalo AltoUSA

Personalised recommendations