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Coloring Fast Without Learning Your Neighbors' Colors

Authors Magnús M. Halldórsson , Fabian Kuhn , Yannic Maus , Alexandre Nolin

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Author Details

Magnús M. Halldórsson
  • Reykjavik University, Iceland
Fabian Kuhn
  • University of Freiburg, Germany
Yannic Maus
  • Technion - Israel Institute of Technology, Haifa, Israel
Alexandre Nolin
  • Reykjavik University, Iceland

Funding

This project was supported by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement no. 755839 and by the Icelandic Research Fund grant 174484.

Cite AsGet BibTex

Magnús M. Halldórsson, Fabian Kuhn, Yannic Maus, and Alexandre Nolin. Coloring Fast Without Learning Your Neighbors' Colors. In 34th International Symposium on Distributed Computing (DISC 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 179, pp. 39:1-39:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)
https://doi.org/10.4230/LIPIcs.DISC.2020.39

Abstract

We give an improved randomized CONGEST algorithm for distance-2 coloring that uses Δ²+1 colors and runs in O(log n) rounds, improving the recent O(log Δ ⋅ log n)-round algorithm in [Halldórsson, Kuhn, Maus; PODC '20]. We then improve the time complexity to O(log Δ) + 2^{O(√{log log n})}.

Subject Classification

ACM Subject Classification
  • Theory of computation → Distributed algorithms
Keywords
  • distributed graph coloring
  • distance 2 coloring
  • congestion

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