分布对称破缺的新技术

Johannes Schneider, Roger Wattenhofer
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引用次数: 113

摘要

本文介绍了分布式算法对称性破缺的一种新技术——Multi-Trials,并将其应用于一般图中的各种问题。例如,我们提出了三种分布式(顶点或边缘)着色的随机算法,改进了以前的算法,并显示了时间/颜色的权衡。获得Δ+1的着色时间为O(log Δ+√log n)。获得O(Δ+log1+1/log*nn)的着色时间为O(log* n)。对于多对数度的图来说,这比时间上的指数级改进要多。我们最快的算法使用O(Δlog(c) n+ log1+1/c n)颜色在常数时间内工作,其中c表示任意常数,log(c) n表示c次(递归地)应用对数ton。我们还使用多重试验技术来计算网络分解和计算最大独立集(MIS),对几个图类获得了新的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A new technique for distributed symmetry breaking
We introduce Multi-Trials, a new technique for symmetry breaking for distributed algorithms and apply it to various problems in general graphs. For instance, we present three randomized algorithms for distributed (vertex or edge) coloring improving on previous algorithms and showing a time/color trade-off. To get a Δ+1 coloring takes time O(log Δ+ √ log n). To obtain an O(Δ+log1+1/log*nn) coloring takes time O(log* n). This is more than an exponential improvement in time for graphs of polylogarithmic degree. Our fastest algorithm works in constant time using O(Δlog(c) n+ log1+1/c n) colors, where c denotes an arbitrary constant and log(c ) n denotes the c times (recursively) applied logarithm ton. We also use the Multi-Trials technique to compute network decompositions and to compute maximal independent set (MIS), obtaining new results for several graph classes.
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