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Distributed Minimum Vertex Coloring and Maximum Independent Set in Chordal Graphs

Authors Christian Konrad, Viktor Zamaraev

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Author Details

Christian Konrad
  • Department of Computer Science, University of Bristol, UK
Viktor Zamaraev
  • Department of Computer Science, Durham University, UK

Funding

  • Konrad, Christian: C.K. carried out most work on this paper while being at the University of Warwick. He was supported by the Centre for Discrete Mathematics and its Applications (DIMAP) at Warwick University and by EPSRC award EP/N011163/1.
  • Zamaraev, Viktor: V.Z. is supported by EPSRC award EP/P020372/1.

Cite AsGet BibTex

Christian Konrad and Viktor Zamaraev. Distributed Minimum Vertex Coloring and Maximum Independent Set in Chordal Graphs. In 44th International Symposium on Mathematical Foundations of Computer Science (MFCS 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 138, pp. 21:1-21:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)
https://doi.org/10.4230/LIPIcs.MFCS.2019.21

Abstract

We give deterministic distributed (1+epsilon)-approximation algorithms for Minimum Vertex Coloring and Maximum Independent Set on chordal graphs in the LOCAL model. Our coloring algorithm runs in O( (1 / epsilon) log n) rounds, and our independent set algorithm has a runtime of O( (1/epsilon) log(1/epsilon)log^* n) rounds. For coloring, existing lower bounds imply that the dependencies on 1/epsilon and log n are best possible. For independent set, we prove that Omega(1/epsilon) rounds are necessary. Both our algorithms make use of the tree decomposition of the input chordal graph. They iteratively peel off interval subgraphs, which are identified via the tree decomposition of the input graph, thereby partitioning the vertex set into O(log n) layers. For coloring, each interval graph is colored independently, which results in various coloring conflicts between the layers. These conflicts are then resolved in a separate phase, using the particular structure of our partitioning. For independent set, only the first O(log (1/epsilon)) layers are required as they already contain a large enough independent set. We develop a (1+epsilon)-approximation maximum independent set algorithm for interval graphs, which we then apply to those layers. This work raises the question as to how useful tree decompositions are for distributed computing.

Subject Classification

ACM Subject Classification
  • Theory of computation → Distributed algorithms
Keywords
  • local model
  • approximation algorithms
  • minimum vertex coloring
  • maximum independent set
  • chordal graphs

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Related Versions

  • This work has previously been presented as a Brief Announcement at PODC 2018. A full version of the paper is available at [Konrad and Zamaraev, 2018], https://arxiv.org/abs/1805.04544.

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