Distributed CONGEST Algorithm for Finding Hamiltonian Paths in Dirac Graphs and Generalizations

Noy Biton, R. Levi, Moti Medina
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Abstract

We study the problem of finding a Hamiltonian cycle under the promise that the input graph has a minimum degree of at least $n/2$, where $n$ denotes the number of vertices in the graph. The classical theorem of Dirac states that such graphs (a.k.a. Dirac graphs) are Hamiltonian, i.e., contain a Hamiltonian cycle. Moreover, finding a Hamiltonian cycle in Dirac graphs can be done in polynomial time in the classical centralized model. This paper presents a randomized distributed CONGEST algorithm that finds w.h.p. a Hamiltonian cycle (as well as maximum matching) within $O(\log n)$ rounds under the promise that the input graph is a Dirac graph. This upper bound is in contrast to general graphs in which both the decision and search variants of Hamiltonicity require $\tilde{\Omega}(n^2)$ rounds, as shown by Bachrach et al. [PODC'19]. In addition, we consider two generalizations of Dirac graphs: Ore graphs and Rahman-Kaykobad graphs [IPL'05]. In Ore graphs, the sum of the degrees of every pair of non-adjacent vertices is at least $n$, and in Rahman-Kaykobad graphs, the sum of the degrees of every pair of non-adjacent vertices plus their distance is at least $n+1$. We show how our algorithm for Dirac graphs can be adapted to work for these more general families of graphs.
Dirac图中寻找哈密顿路径的分布式CONGEST算法及其推广
我们研究了在输入图的最小度至少为$n/2$的情况下寻找哈密顿循环的问题,其中$n$表示图中的顶点数。狄拉克经典定理指出,这样的图(又称狄拉克图)是哈密顿图,即包含哈密顿循环。此外,在经典的集中模型中,在多项式时间内可以找到狄拉克图中的哈密顿循环。本文提出了一种随机分布的CONGEST算法,该算法在保证输入图是狄拉克图的情况下,在$O(\log n)$轮内找到w.h.p.一个哈密顿循环(以及最大匹配)。这个上界与一般图相反,在一般图中,哈密顿性的决策和搜索变体都需要$\tilde{\Omega}(n^2)$轮数,如Bachrach等人[PODC'19]所示。此外,我们考虑了狄拉克图的两种推广:Ore图和Rahman-Kaykobad图[IPL'05]。在Ore图中,每对不相邻顶点的度数之和至少为$n$,而在Rahman-Kaykobad图中,每对不相邻顶点的度数之和加上它们的距离至少为$n+1$。我们将展示我们的狄拉克图算法如何适用于这些更一般的图族。
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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