381 research outputs found

    Optimal decremental connectivity in planar graphs

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    We show an algorithm for dynamic maintenance of connectivity information in an undirected planar graph subject to edge deletions. Our algorithm may answer connectivity queries of the form `Are vertices uu and vv connected with a path?' in constant time. The queries can be intermixed with any sequence of edge deletions, and the algorithm handles all updates in O(n)O(n) time. This results improves over previously known O(nlog⁥n)O(n \log n) time algorithm

    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(log⁥4n/log⁥log⁥n)O(\log^4n/\log\log n) amortized time per operation, improving the O(log⁥4n)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

    Reliable Hubs for Partially-Dynamic All-Pairs Shortest Paths in Directed Graphs

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    We give new partially-dynamic algorithms for the all-pairs shortest paths problem in weighted directed graphs. Most importantly, we give a new deterministic incremental algorithm for the problem that handles updates in O~(mn^(4/3) log{W}/epsilon) total time (where the edge weights are from [1,W]) and explicitly maintains a (1+epsilon)-approximate distance matrix. For a fixed epsilon>0, this is the first deterministic partially dynamic algorithm for all-pairs shortest paths in directed graphs, whose update time is o(n^2) regardless of the number of edges. Furthermore, we also show how to improve the state-of-the-art partially dynamic randomized algorithms for all-pairs shortest paths [Baswana et al. STOC\u2702, Bernstein STOC\u2713] from Monte Carlo randomized to Las Vegas randomized without increasing the running time bounds (with respect to the O~(*) notation). Our results are obtained by giving new algorithms for the problem of dynamically maintaining hubs, that is a set of O~(n/d) vertices which hit a shortest path between each pair of vertices, provided it has hop-length Omega(d). We give new subquadratic deterministic and Las Vegas algorithms for maintenance of hubs under either edge insertions or deletions

    Dynamic Approximate All-Pairs Shortest Paths: Breaking the O(mn) Barrier and Derandomization

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    We study dynamic (1+Ï”)(1+\epsilon)-approximation algorithms for the all-pairs shortest paths problem in unweighted undirected nn-node mm-edge graphs under edge deletions. The fastest algorithm for this problem is a randomized algorithm with a total update time of O~(mn/Ï”)\tilde O(mn/\epsilon) and constant query time by Roditty and Zwick [FOCS 2004]. The fastest deterministic algorithm is from a 1981 paper by Even and Shiloach [JACM 1981]; it has a total update time of O(mn2)O(mn^2) and constant query time. We improve these results as follows: (1) We present an algorithm with a total update time of O~(n5/2/Ï”)\tilde O(n^{5/2}/\epsilon) and constant query time that has an additive error of 22 in addition to the 1+Ï”1+\epsilon multiplicative error. This beats the previous O~(mn/Ï”)\tilde O(mn/\epsilon) time when m=Ω(n3/2)m=\Omega(n^{3/2}). Note that the additive error is unavoidable since, even in the static case, an O(n3−ή)O(n^{3-\delta})-time (a so-called truly subcubic) combinatorial algorithm with 1+Ï”1+\epsilon multiplicative error cannot have an additive error less than 2−ϔ2-\epsilon, unless we make a major breakthrough for Boolean matrix multiplication [Dor et al. FOCS 1996] and many other long-standing problems [Vassilevska Williams and Williams FOCS 2010]. The algorithm can also be turned into a (2+Ï”)(2+\epsilon)-approximation algorithm (without an additive error) with the same time guarantees, improving the recent (3+Ï”)(3+\epsilon)-approximation algorithm with O~(n5/2+O(log⁥(1/Ï”)/log⁥n))\tilde O(n^{5/2+O(\sqrt{\log{(1/\epsilon)}/\log n})}) running time of Bernstein and Roditty [SODA 2011] in terms of both approximation and time guarantees. (2) We present a deterministic algorithm with a total update time of O~(mn/Ï”)\tilde O(mn/\epsilon) and a query time of O(log⁥log⁥n)O(\log\log n). The algorithm has a multiplicative error of 1+Ï”1+\epsilon and gives the first improved deterministic algorithm since 1981. It also answers an open question raised by Bernstein [STOC 2013].Comment: A preliminary version was presented at the 2013 IEEE 54th Annual Symposium on Foundations of Computer Science (FOCS 2013

    Dynamic Dominators and Low-High Orders in DAGs

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    We consider practical algorithms for maintaining the dominator tree and a low-high order in directed acyclic graphs (DAGs) subject to dynamic operations. Let G be a directed graph with a distinguished start vertex s. The dominator tree D of G is a tree rooted at s, such that a vertex v is an ancestor of a vertex w if and only if all paths from s to w in G include v. The dominator tree is a central tool in program optimization and code generation, and has many applications in other diverse areas including constraint programming, circuit testing, biology, and in algorithms for graph connectivity problems. A low-high order of G is a preorder of D that certifies the correctness of D, and has further applications in connectivity and path-determination problems. We first provide a practical and carefully engineered version of a recent algorithm [ICALP 2017] for maintaining the dominator tree of a DAG through a sequence of edge deletions. The algorithm runs in O(mn) total time and O(m) space, where n is the number of vertices and m is the number of edges before any deletion. In addition, we present a new algorithm that maintains a low-high order of a DAG under edge deletions within the same bounds. Both results extend to the case of reducible graphs (a class that includes DAGs). Furthermore, we present a fully dynamic algorithm for maintaining the dominator tree of a DAG under an intermixed sequence of edge insertions and deletions. Although it does not maintain the O(mn) worst-case bound of the decremental algorithm, our experiments highlight that the fully dynamic algorithm performs very well in practice. Finally, we study the practical efficiency of all our algorithms by conducting an extensive experimental study on real-world and synthetic graphs

    Decremental Single-Source Reachability in Planar Digraphs

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    In this paper we show a new algorithm for the decremental single-source reachability problem in directed planar graphs. It processes any sequence of edge deletions in O(nlog⁥2nlog⁥log⁥n)O(n\log^2{n}\log\log{n}) total time and explicitly maintains the set of vertices reachable from a fixed source vertex. Hence, if all edges are eventually deleted, the amortized time of processing each edge deletion is only O(log⁥2nlog⁥log⁥n)O(\log^2 n \log \log n), which improves upon a previously known O(n)O(\sqrt{n}) solution. We also show an algorithm for decremental maintenance of strongly connected components in directed planar graphs with the same total update time. These results constitute the first almost optimal (up to polylogarithmic factors) algorithms for both problems. To the best of our knowledge, these are the first dynamic algorithms with polylogarithmic update times on general directed planar graphs for non-trivial reachability-type problems, for which only polynomial bounds are known in general graphs

    Good r-Divisions Imply Optimal Amortized Decremental Biconnectivity

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    We present a data structure that, given a graph G of n vertices and m edges, and a suitable pair of nested r-divisions of G, preprocesses G in O(m+n) time and handles any series of edge-deletions in O(m) total time while answering queries to pairwise biconnectivity in worst-case O(1) time. In case the vertices are not biconnected, the data structure can return a cutvertex separating them in worst-case O(1) time. As an immediate consequence, this gives optimal amortized decremental biconnectivity, 2-edge connectivity, and connectivity for large classes of graphs, including planar graphs and other minor free graphs
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