亚线性时间内的精确分布最短路径

Michael Elkin
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引用次数: 74

摘要

分布式单源最短路径问题是消息传递分布式计算中最基本、最核心的问题之一。经典Bellman-Ford算法在O(n)时间内求解该问题,其中n为输入图g中的顶点数。Peleg和Rubinovich, FOCS'99给出了该问题的下界Ω(D +√n),其中D为g的跳直径。当D相对较小时,该问题能否在O(n)时间内求解是一个著名的开放问题。尽管对这个问题的近似变体进行了深入的研究,得出了接近最优的算法,但对于原始问题却没有任何进展。本文对这个问题作了肯定的回答。我们设计了一个需要O((n logn)5/6)时间的算法,对于D = O(√n logn)和O(D1/3 #183;(n logn)2/3)时间,对于更大的D,这个运行时间在n中几乎在整个参数范围内都是次线性的,特别是对于D = o(n/ log2n)。我们还在两个方向上推广我们的结果。一类是边带宽b≥1,另一类是s源最短路径问题。对于前一个问题,与单位带宽情况相比,我们的算法提供了一个改进的边界。特别地,我们提供了一个全对最短路径算法,该算法需要O(n5/3 #183;对于d的所有值,即使b = 1,也需要log2/3 (n)的时间。对于后一个问题(s个源),我们的算法还提供了在整个参数范围内改进之前的最新技术的边界。从技术角度来看,我们的算法在不首先计算G '本身的情况下,计算G的骨架图G '的hopset G″。然后我们在G '∪G″中进行Bellman-Ford探索,同时动态计算G '的所需边。因此,我们的算法精确地计算它真正需要的G '的那些边,而不是近似地计算整个G '。
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Distributed exact shortest paths in sublinear time
The distributed single-source shortest paths problem is one of the most fundamental and central problems in the message-passing distributed computing. Classical Bellman-Ford algorithm solves it in O(n) time, where n is the number of vertices in the input graph G. Peleg and Rubinovich, FOCS'99, showed a lower bound of Ω(D + √n) for this problem, where D is the hop-diameter of G. Whether or not this problem can be solved in o(n) time when D is relatively small is a major notorious open question. Despite intensive research that yielded near-optimal algorithms for the approximate variant of this problem, no progress was reported for the original problem. In this paper we answer this question in the affirmative. We devise an algorithm that requires O((n logn)5/6) time, for D = O(√n logn), and O(D1/3 #183; (n logn)2/3) time, for larger D. This running time is sublinear in n in almost the entire range of parameters, specifically, for D = o(n/log2 n). We also generalize our result in two directions. One is when edges have bandwidth b ≥ 1, and the other is the s-sources shortest paths problem. For the former problem, our algorithm provides an improved bound, compared to the unit-bandwidth case. In particular, we provide an all-pairs shortest paths algorithm that requires O(n5/3 #183; log2/3 n) time, even for b = 1, for all values of D. For the latter problem (of s sources), our algorithm also provides bounds that improve upon the previous state-of-the-art in the entire range of parameters. From the technical viewpoint, our algorithm computes a hopset G″ of a skeleton graph G′ of G without first computing G′ itself. We then conduct a Bellman-Ford exploration in G′ ∪ G″, while computing the required edges of G′ on the fly. As a result, our algorithm computes exactly those edges of G′ that it really needs, rather than computing approximately the entire G′.
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