776 research outputs found

    Approximate Distance Oracles for Planar Graphs with Improved Query Time-Space Tradeoff

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    We consider approximate distance oracles for edge-weighted n-vertex undirected planar graphs. Given fixed epsilon > 0, we present a (1+epsilon)-approximate distance oracle with O(n(loglog n)^2) space and O((loglog n)^3) query time. This improves the previous best product of query time and space of the oracles of Thorup (FOCS 2001, J. ACM 2004) and Klein (SODA 2002) from O(n log n) to O(n(loglog n)^5).Comment: 20 pages, 9 figures of which 2 illustrate pseudo-code. This is the SODA 2016 version but with the definition of C_i in Phase I fixed and the analysis slightly modified accordingly. The main change is in the subsection bounding query time and stretch for Phase

    Minimum Cycle Basis and All-Pairs Min Cut of a Planar Graph in Subquadratic Time

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    A minimum cycle basis of a weighted undirected graph GG is a basis of the cycle space of GG such that the total weight of the cycles in this basis is minimized. If GG is a planar graph with non-negative edge weights, such a basis can be found in O(n2)O(n^2) time and space, where nn is the size of GG. We show that this is optimal if an explicit representation of the basis is required. We then present an O(n3/2logn)O(n^{3/2}\log n) time and O(n3/2)O(n^{3/2}) space algorithm that computes a minimum cycle basis \emph{implicitly}. From this result, we obtain an output-sensitive algorithm that explicitly computes a minimum cycle basis in O(n3/2logn+C)O(n^{3/2}\log n + C) time and O(n3/2+C)O(n^{3/2} + C) space, where CC is the total size (number of edges and vertices) of the cycles in the basis. These bounds reduce to O(n3/2logn)O(n^{3/2}\log n) and O(n3/2)O(n^{3/2}), respectively, when GG is unweighted. We get similar results for the all-pairs min cut problem since it is dual equivalent to the minimum cycle basis problem for planar graphs. We also obtain O(n3/2logn)O(n^{3/2}\log n) time and O(n3/2)O(n^{3/2}) space algorithms for finding, respectively, the weight vector and a Gomory-Hu tree of GG. The previous best time and space bound for these two problems was quadratic. From our Gomory-Hu tree algorithm, we obtain the following result: with O(n3/2logn)O(n^{3/2}\log n) time and O(n3/2)O(n^{3/2}) space for preprocessing, the weight of a min cut between any two given vertices of GG can be reported in constant time. Previously, such an oracle required quadratic time and space for preprocessing. The oracle can also be extended to report the actual cut in time proportional to its size

    Faster Deterministic Fully-Dynamic Graph Connectivity

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    We give new deterministic bounds for fully-dynamic graph connectivity. Our data structure supports updates (edge insertions/deletions) in O(log2n/loglogn)O(\log^2n/\log\log n) amortized time and connectivity queries in O(logn/loglogn)O(\log n/\log\log n) worst-case time, where nn is the number of vertices of the graph. This improves the deterministic data structures of Holm, de Lichtenberg, and Thorup (STOC 1998, J.ACM 2001) and Thorup (STOC 2000) which both have O(log2n)O(\log^2n) amortized update time and O(logn/loglogn)O(\log n/\log\log n) worst-case query time. Our model of computation is the same as that of Thorup, i.e., a pointer machine with standard AC0AC^0 instructions.Comment: To appear at SODA 2013. 19 pages, 1 figur

    Faster Fully-Dynamic Minimum Spanning Forest

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    We give a new data structure for the fully-dynamic minimum spanning forest problem in simple graphs. Edge updates are supported in O(log4n/loglogn)O(\log^4n/\log\log n) amortized time per operation, improving the O(log4n)O(\log^4n) amortized bound of Holm et al. (STOC'98, JACM'01). We assume the Word-RAM model with standard instructions.Comment: 13 pages, 2 figure
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