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Ultrafast Distributed Coloring of High Degree Graphs

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arxiv 2105.04700 v1 pith:GCFJF55I submitted 2021-05-10 cs.DC cs.DS

classification cs.DCcs.DS
keywords algorithmcoloringdeltagraphscomplexitycongestdegreedistributed
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abstract

We give a new randomized distributed algorithm for the $\Delta+1$-list coloring problem. The algorithm and its analysis dramatically simplify the previous best result known of Chang, Li, and Pettie [SICOMP 2020]. This allows for numerous refinements, and in particular, we can color all $n$-node graphs of maximum degree $\Delta \ge \log^{2+\Omega(1)} n$ in $O(\log^* n)$ rounds. The algorithm works in the CONGEST model, i.e., it uses only $O(\log n)$ bits per message for communication. On low-degree graphs, the algorithm shatters the graph into components of size $\operatorname{poly}(\log n)$ in $O(\log^* \Delta)$ rounds, showing that the randomized complexity of $\Delta+1$-list coloring in CONGEST depends inherently on the deterministic complexity of related coloring problems.

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  1. Faster Dynamic $(\Delta+1)$-Coloring Against Adaptive Adversaries

    cs.DS 2025-04 conditional novelty 7.0 of 10

    A randomized dynamic algorithm maintains a proper (Δ+1)-coloring against adaptive adversaries in Õ(n^{2/3}) amortized update time, improving the prior Õ(n^{8/9}) bound.

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