Fast Distributed Brooks' Theorem

Manuela Fischer, Yannic Maus, Magn'us M. Halld'orsson
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引用次数: 6

Abstract

We give a randomized $\Delta$-coloring algorithm in the LOCAL model that runs in $\text{poly} \log \log n$ rounds, where $n$ is the number of nodes of the input graph and $\Delta$ is its maximum degree. This means that randomized $\Delta$-coloring is a rare distributed coloring problem with an upper and lower bound in the same ballpark, $\text{poly}\log\log n$, given the known $\Omega(\log_\Delta\log n)$ lower bound [Brandt et al., STOC '16]. Our main technical contribution is a constant time reduction to a constant number of $(\text{deg}+1)$-list coloring instances, for $\Delta = \omega(\log^4 n)$, resulting in a $\text{poly} \log\log n$-round CONGEST algorithm for such graphs. This reduction is of independent interest for other settings, including providing a new proof of Brooks' theorem for high degree graphs, and leading to a constant-round Congested Clique algorithm in such graphs. When $\Delta=\omega(\log^{21} n)$, our algorithm even runs in $O(\log^* n)$ rounds, showing that the base in the $\Omega(\log_\Delta\log n)$ lower bound is unavoidable. Previously, the best LOCAL algorithm for all considered settings used a logarithmic number of rounds. Our result is the first CONGEST algorithm for $\Delta$-coloring non-constant degree graphs.
快速分布布鲁克斯定理
我们在LOCAL模型中给出一个随机的$\Delta$ -着色算法,该算法运行$\text{poly} \log \log n$轮,其中$n$是输入图的节点数,$\Delta$是其最大度。这意味着随机$\Delta$ -着色是一种罕见的分布着色问题,在已知$\Omega(\log_\Delta\log n)$下界的情况下,在相同的范围内具有上界和下界$\text{poly}\log\log n$ [Brandt等人,STOC '16]。我们的主要技术贡献是将时间减少到恒定数量的$(\text{deg}+1)$ -list着色实例(对于$\Delta = \omega(\log^4 n)$),从而产生用于此类图的$\text{poly} \log\log n$ -round CONGEST算法。这种约简对于其他设置具有独立的意义,包括为高次图提供布鲁克斯定理的新证明,并在此类图中导致常轮拥塞团算法。当$\Delta=\omega(\log^{21} n)$时,我们的算法甚至运行$O(\log^* n)$轮,这表明$\Omega(\log_\Delta\log n)$下界的底数是不可避免的。以前,对于所有考虑的设置,最好的LOCAL算法使用对数轮数。我们的结果是$\Delta$ -着色非常次图的第一个CONGEST算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
6.50
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