58,401 research outputs found

    Distributed Approximation Algorithms for Weighted Shortest Paths

    Full text link
    A distributed network is modeled by a graph having nn nodes (processors) and diameter DD. We study the time complexity of approximating {\em weighted} (undirected) shortest paths on distributed networks with a O(logn)O(\log n) {\em bandwidth restriction} on edges (the standard synchronous \congest model). The question whether approximation algorithms help speed up the shortest paths (more precisely distance computation) was raised since at least 2004 by Elkin (SIGACT News 2004). The unweighted case of this problem is well-understood while its weighted counterpart is fundamental problem in the area of distributed approximation algorithms and remains widely open. We present new algorithms for computing both single-source shortest paths (\sssp) and all-pairs shortest paths (\apsp) in the weighted case. Our main result is an algorithm for \sssp. Previous results are the classic O(n)O(n)-time Bellman-Ford algorithm and an O~(n1/2+1/2k+D)\tilde O(n^{1/2+1/2k}+D)-time (8klog(k+1)1)(8k\lceil \log (k+1) \rceil -1)-approximation algorithm, for any integer k1k\geq 1, which follows from the result of Lenzen and Patt-Shamir (STOC 2013). (Note that Lenzen and Patt-Shamir in fact solve a harder problem, and we use O~()\tilde O(\cdot) to hide the O(\poly\log n) term.) We present an O~(n1/2D1/4+D)\tilde O(n^{1/2}D^{1/4}+D)-time (1+o(1))(1+o(1))-approximation algorithm for \sssp. This algorithm is {\em sublinear-time} as long as DD is sublinear, thus yielding a sublinear-time algorithm with almost optimal solution. When DD is small, our running time matches the lower bound of Ω~(n1/2+D)\tilde \Omega(n^{1/2}+D) by Das Sarma et al. (SICOMP 2012), which holds even when D=Θ(logn)D=\Theta(\log n), up to a \poly\log n factor.Comment: Full version of STOC 201

    Distributed Exact Shortest Paths in Sublinear Time

    Full text link
    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)O(n) time, where nn is the number of vertices in the input graph GG. Peleg and Rubinovich (FOCS'99) showed a lower bound of Ω~(D+n)\tilde{\Omega}(D + \sqrt{n}) for this problem, where DD is the hop-diameter of GG. Whether or not this problem can be solved in o(n)o(n) time when DD is relatively small is a major notorious open question. Despite intensive research \cite{LP13,N14,HKN15,EN16,BKKL16} 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((nlogn)5/6)O((n \log n)^{5/6}) time, for D=O(nlogn)D = O(\sqrt{n \log n}), and O(D1/3(nlogn)2/3)O(D^{1/3} \cdot (n \log n)^{2/3}) time, for larger DD. This running time is sublinear in nn in almost the entire range of parameters, specifically, for D=o(n/log2n)D = o(n/\log^2 n). For the all-pairs shortest paths problem, our algorithm requires O(n5/3log2/3n)O(n^{5/3} \log^{2/3} n) time, regardless of the value of DD. We also devise the first algorithm with non-trivial complexity guarantees for computing exact shortest paths in the multipass semi-streaming model of computation. From the technical viewpoint, our algorithm computes a hopset G"G" of a skeleton graph GG' of GG without first computing GG' itself. We then conduct a Bellman-Ford exploration in GG"G' \cup G", while computing the required edges of GG' on the fly. As a result, our algorithm computes exactly those edges of GG' that it really needs, rather than computing approximately the entire GG'

    The Complexity of Rerouting Shortest Paths

    Get PDF
    The Shortest Path Reconfiguration problem has as input a graph G (with unit edge lengths) with vertices s and t, and two shortest st-paths P and Q. The question is whether there exists a sequence of shortest st-paths that starts with P and ends with Q, such that subsequent paths differ in only one vertex. This is called a rerouting sequence. This problem is shown to be PSPACE-complete. For claw-free graphs and chordal graphs, it is shown that the problem can be solved in polynomial time, and that shortest rerouting sequences have linear length. For these classes, it is also shown that deciding whether a rerouting sequence exists between all pairs of shortest st-paths can be done in polynomial time. Finally, a polynomial time algorithm for counting the number of isolated paths is given.Comment: The results on claw-free graphs, chordal graphs and isolated paths have been added in version 2 (april 2012). Version 1 (September 2010) only contained the PSPACE-hardness result. (Version 2 has been submitted.
    corecore