Improved Distributed Algorithms for Exact Shortest Paths
Mohsen Ghaffari, Jason Li

TL;DR
This paper introduces a new distributed algorithm for exact single-source shortest paths that improves complexity bounds, especially for directed graphs, and extends to multiple sources, advancing the state of the art in distributed shortest path computation.
Contribution
It presents the first sublinear-time distributed algorithm for exact shortest paths in directed graphs and improves existing bounds for undirected graphs, extending to multiple sources.
Findings
Achieves $ ilde O(n^{3/4}D^{1/4})$ complexity for undirected graphs.
Provides a sublinear-time algorithm for directed graphs.
Extends to exact $oldsymbol{ ext{k}}$-source shortest paths.
Abstract
Computing shortest paths is one of the central problems in the theory of distributed computing. For the last few years, substantial progress has been made on the approximate single source shortest paths problem, culminating in an algorithm of Becker et al. [DISC'17] which deterministically computes -approximate shortest paths in time, where is the hop-diameter of the graph. Up to logarithmic factors, this time complexity is optimal, matching the lower bound of Elkin [STOC'04]. The question of exact shortest paths however saw no algorithmic progress for decades, until the recent breakthrough of Elkin [STOC'17], which established a sublinear-time algorithm for exact single source shortest paths on undirected graphs. Shortly after, Huang et al. [FOCS'17] provided improved algorithms for exact all pairs shortest paths problem on directed graphs. In…
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Taxonomy
TopicsCryptography and Data Security · Privacy-Preserving Technologies in Data · Complexity and Algorithms in Graphs
