Gopal Pandurangan, Peter Robinson, Michele Scquizzato
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引用次数: 50
摘要
本文提出了一种随机(Las Vegas)分布式算法,该算法在时间和消息复杂度最优的加权网络中构造最小生成树(MST)。该算法运行时间为Õ(D +√n),交换消息为Õ(m)条(均为大概率),其中n为网络节点数,D为直径,m为边数。这是第一个同时匹配Ω(D +√n)的时间下界[Elkin, SIAM J. Comput. 2006]和Ω(m)的消息下界[Kutten et al., J. ACM 2015]的分布式MST算法,两者都适用于随机蒙特卡罗算法。使用两种完全不同的图结构推导了先验时间和消息下界;显示一个下界的现有下界构造不适用于另一个下界。为了补充我们的算法,我们提出了一个新的下界图构造,其中任何分布式MST算法都需要Ω(D +√n)轮和Ω(m)消息。
A time- and message-optimal distributed algorithm for minimum spanning trees
This paper presents a randomized (Las Vegas) distributed algorithm that constructs a minimum spanning tree (MST) in weighted networks with optimal (up to polylogarithmic factors) time and message complexity. This algorithm runs in Õ(D + √n) time and exchanges Õ(m) messages (both with high probability), where n is the number of nodes of the network, D is the diameter, and m is the number of edges. This is the first distributed MST algorithm that matches simultaneously the time lower bound of Ω(D + √n) [Elkin, SIAM J. Comput. 2006] and the message lower bound of Ω(m) [Kutten et al., J. ACM 2015], which both apply to randomized Monte Carlo algorithms. The prior time and message lower bounds are derived using two completely different graph constructions; the existing lower bound construction that shows one lower bound does not work for the other. To complement our algorithm, we present a new lower bound graph construction for which any distributed MST algorithm requires both Ω(D + √n) rounds and Ω(m) messages.