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    Exact Distance Oracles for Planar Graphs

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    We present new and improved data structures that answer exact node-to-node distance queries in planar graphs. Such data structures are also known as distance oracles. For any directed planar graph on n nodes with non-negative lengths we obtain the following: * Given a desired space allocation S∈[nlg⁑lg⁑n,n2]S\in[n\lg\lg n,n^2], we show how to construct in O~(S)\tilde O(S) time a data structure of size O(S)O(S) that answers distance queries in O~(n/S)\tilde O(n/\sqrt S) time per query. As a consequence, we obtain an improvement over the fastest algorithm for k-many distances in planar graphs whenever k∈[n,n)k\in[\sqrt n,n). * We provide a linear-space exact distance oracle for planar graphs with query time O(n1/2+eps)O(n^{1/2+eps}) for any constant eps>0. This is the first such data structure with provable sublinear query time. * For edge lengths at least one, we provide an exact distance oracle of space O~(n)\tilde O(n) such that for any pair of nodes at distance D the query time is O~(minD,n)\tilde O(min {D,\sqrt n}). Comparable query performance had been observed experimentally but has never been explained theoretically. Our data structures are based on the following new tool: given a non-self-crossing cycle C with c=O(n)c = O(\sqrt n) nodes, we can preprocess G in O~(n)\tilde O(n) time to produce a data structure of size O(nlg⁑lg⁑c)O(n \lg\lg c) that can answer the following queries in O~(c)\tilde O(c) time: for a query node u, output the distance from u to all the nodes of C. This data structure builds on and extends a related data structure of Klein (SODA'05), which reports distances to the boundary of a face, rather than a cycle. The best distance oracles for planar graphs until the current work are due to Cabello (SODA'06), Djidjev (WG'96), and Fakcharoenphol and Rao (FOCS'01). For Οƒβˆˆ(1,4/3)\sigma\in(1,4/3) and space S=nΟƒS=n^\sigma, we essentially improve the query time from n2/Sn^2/S to n2/S\sqrt{n^2/S}.Comment: To appear in the proceedings of the 23rd ACM-SIAM Symposium on Discrete Algorithms, SODA 201
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