In this paper we present a deterministic CONGEST algorithm to compute an $O(k\Delta)$-vertex coloring in $O(\Delta/k)+\log^* n$ rounds, where $\Delta$ is the maximum degree of the network graph and $1\leq k\leq O(\Delta)$ can be freely chosen. The algorithm is extremely simple: Each node locally computes a sequence of colors and then it "tries colors" from the sequence in batches of size $k$. Our algorithm subsumes many important results in the history of distributed graph coloring as special cases, including Linial's color reduction [Linial, FOCS'87], the celebrated locally iterative algorithm from [Barenboim, Elkin, Goldenberg, PODC'18], and various algorithms to compute defective and arbdefective colorings. Our algorithm can smoothly scale between these and also simplifies the state of the art $(\Delta+1)$-coloring algorithm. At the cost of losing the full algorithm's simplicity we also provide a $O(k\Delta)$-coloring algorithm in $O(\sqrt{\Delta/k})+\log^* n$ rounds. We also provide improved deterministic algorithms for ruling sets, and, additionally, we provide a tight characterization for one-round color reduction algorithms.
翻译:在本文中, 我们提出一个确定性的 CONGEST 算法, 用来计算$O( k\ Delta) $( delta/ k) 的反向色彩。 我们的算法在以美元为单位的分布式图表颜色的历史上有许多重要结果, 包括 Linial 的颜色减少 [Linal, FOCS'87], 来自 [Barenboim, Elkin, Goldenberg, PODC' 18] 的庆祝本地迭代算法, 以及用于计算缺陷和偏差颜色的各种算法。 我们的算法可以在这些序列中平稳地计算颜色, 然后将颜色从以美元(\ Delta+1) 的序列中“ 扭曲 ” 。 我们的算法可以将分布式图表颜色作为特殊案例, 包括 Linial 的颜色减少 [Linial, FOCS'87] 、 来自[Barenboim, Elkin, Goldberg, PoDC' 18] 的当地迭代算算法, 也提供了一种简化的算算算算算算。</s>