237 research outputs found

    A Faster Distributed Single-Source Shortest Paths Algorithm

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    We devise new algorithms for the single-source shortest paths (SSSP) problem with non-negative edge weights in the CONGEST model of distributed computing. While close-to-optimal solutions, in terms of the number of rounds spent by the algorithm, have recently been developed for computing SSSP approximately, the fastest known exact algorithms are still far away from matching the lower bound of Ω~(n+D) \tilde \Omega (\sqrt{n} + D) rounds by Peleg and Rubinovich [SIAM Journal on Computing 2000], where n n is the number of nodes in the network and D D is its diameter. The state of the art is Elkin's randomized algorithm [STOC 2017] that performs O~(n2/3D1/3+n5/6) \tilde O(n^{2/3} D^{1/3} + n^{5/6}) rounds. We significantly improve upon this upper bound with our two new randomized algorithms for polynomially bounded integer edge weights, the first performing O~(nD) \tilde O (\sqrt{n D}) rounds and the second performing O~(nD1/4+n3/5+D) \tilde O (\sqrt{n} D^{1/4} + n^{3/5} + D) rounds. Our bounds also compare favorably to the independent result by Ghaffari and Li [STOC 2018]. As side results, we obtain a (1+ϵ) (1 + \epsilon) -approximation O~((nD1/4+D)/ϵ) \tilde O ((\sqrt{n} D^{1/4} + D) / \epsilon) -round algorithm for directed SSSP and a new work/depth trade-off for exact SSSP on directed graphs in the PRAM model.Comment: Presented at the the 59th Annual IEEE Symposium on Foundations of Computer Science (FOCS 2018

    Near-Optimal Approximate Shortest Paths and Transshipment in Distributed and Streaming Models

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    We present a method for solving the transshipment problem - also known as uncapacitated minimum cost flow - up to a multiplicative error of 1+ε1 + \varepsilon in undirected graphs with non-negative edge weights using a tailored gradient descent algorithm. Using O~()\tilde{O}(\cdot) to hide polylogarithmic factors in nn (the number of nodes in the graph), our gradient descent algorithm takes O~(ε2)\tilde O(\varepsilon^{-2}) iterations, and in each iteration it solves an instance of the transshipment problem up to a multiplicative error of polylogn\operatorname{polylog} n. In particular, this allows us to perform a single iteration by computing a solution on a sparse spanner of logarithmic stretch. Using a randomized rounding scheme, we can further extend the method to finding approximate solutions for the single-source shortest paths (SSSP) problem. As a consequence, we improve upon prior work by obtaining the following results: (1) Broadcast CONGEST model: (1+ε)(1 + \varepsilon)-approximate SSSP using O~((n+D)ε3)\tilde{O}((\sqrt{n} + D)\varepsilon^{-3}) rounds, where D D is the (hop) diameter of the network. (2) Broadcast congested clique model: (1+ε)(1 + \varepsilon)-approximate transshipment and SSSP using O~(ε2)\tilde{O}(\varepsilon^{-2}) rounds. (3) Multipass streaming model: (1+ε)(1 + \varepsilon)-approximate transshipment and SSSP using O~(n)\tilde{O}(n) space and O~(ε2)\tilde{O}(\varepsilon^{-2}) passes. The previously fastest SSSP algorithms for these models leverage sparse hop sets. We bypass the hop set construction; computing a spanner is sufficient with our method. The above bounds assume non-negative edge weights that are polynomially bounded in nn; for general non-negative weights, running times scale with the logarithm of the maximum ratio between non-zero weights.Comment: Accepted to SIAM Journal on Computing. Preliminary version in DISC 2017. Abstract shortened to fit arXiv's limitation to 1920 character

    A Distributed Algorithm for Directed Minimum-Weight Spanning Tree

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    Reachability and Shortest Paths in the Broadcast CONGEST Model

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    In this paper we study the time complexity of the single-source reachability problem and the single-source shortest path problem for directed unweighted graphs in the Broadcast CONGEST model. We focus on the case where the diameter D of the underlying network is constant. We show that for the case where D = 1 there is, quite surprisingly, a very simple algorithm that solves the reachability problem in 1(!) round. In contrast, for networks with D = 2, we show that any distributed algorithm (possibly randomized) for this problem requires Omega(sqrt{n/ log{n}}) rounds. Our results therefore completely resolve (up to a small polylog factor) the complexity of the single-source reachability problem for a wide range of diameters. Furthermore, we show that when D = 1, it is even possible to get an almost 3 - approximation for the all-pairs shortest path problem (for directed unweighted graphs) in just 2 rounds. We also prove a stronger lower bound of Omega(sqrt{n}) for the single-source shortest path problem for unweighted directed graphs that holds even when the diameter of the underlying network is 2. As far as we know this is the first lower bound that achieves Omega(sqrt{n}) for this problem
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