937 research outputs found

    Recognizing Weighted Disk Contact Graphs

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    Disk contact representations realize graphs by mapping vertices bijectively to interior-disjoint disks in the plane such that two disks touch each other if and only if the corresponding vertices are adjacent in the graph. Deciding whether a vertex-weighted planar graph can be realized such that the disks' radii coincide with the vertex weights is known to be NP-hard. In this work, we reduce the gap between hardness and tractability by analyzing the problem for special graph classes. We show that it remains NP-hard for outerplanar graphs with unit weights and for stars with arbitrary weights, strengthening the previous hardness results. On the positive side, we present constructive linear-time recognition algorithms for caterpillars with unit weights and for embedded stars with arbitrary weights.Comment: 24 pages, 21 figures, extended version of a paper to appear at the International Symposium on Graph Drawing and Network Visualization (GD) 201

    Better Tradeoffs for Exact Distance Oracles in Planar Graphs

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    We present an O(n1.5)O(n^{1.5})-space distance oracle for directed planar graphs that answers distance queries in O(logn)O(\log n) time. Our oracle both significantly simplifies and significantly improves the recent oracle of Cohen-Addad, Dahlgaard and Wulff-Nilsen [FOCS 2017], which uses O(n5/3)O(n^{5/3})-space and answers queries in O(logn)O(\log n) time. We achieve this by designing an elegant and efficient point location data structure for Voronoi diagrams on planar graphs. We further show a smooth tradeoff between space and query-time. For any S[n,n2]S\in [n,n^2], we show an oracle of size SS that answers queries in O~(max{1,n1.5/S})\tilde O(\max\{1,n^{1.5}/S\}) time. This new tradeoff is currently the best (up to polylogarithmic factors) for the entire range of SS and improves by polynomial factors over all the previously known tradeoffs for the range S[n,n5/3]S \in [n,n^{5/3}]

    Advanced Multilevel Node Separator Algorithms

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    A node separator of a graph is a subset S of the nodes such that removing S and its incident edges divides the graph into two disconnected components of about equal size. In this work, we introduce novel algorithms to find small node separators in large graphs. With focus on solution quality, we introduce novel flow-based local search algorithms which are integrated in a multilevel framework. In addition, we transfer techniques successfully used in the graph partitioning field. This includes the usage of edge ratings tailored to our problem to guide the graph coarsening algorithm as well as highly localized local search and iterated multilevel cycles to improve solution quality even further. Experiments indicate that flow-based local search algorithms on its own in a multilevel framework are already highly competitive in terms of separator quality. Adding additional local search algorithms further improves solution quality. Our strongest configuration almost always outperforms competing systems while on average computing 10% and 62% smaller separators than Metis and Scotch, respectively

    Faster Separators for Shallow Minor-Free Graphs via Dynamic Approximate Distance Oracles

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    Plotkin, Rao, and Smith (SODA'97) showed that any graph with mm edges and nn vertices that excludes KhK_h as a depth O(logn)O(\ell\log n)-minor has a separator of size O(n/+h2logn)O(n/\ell + \ell h^2\log n) and that such a separator can be found in O(mn/)O(mn/\ell) time. A time bound of O(m+n2+ϵ/)O(m + n^{2+\epsilon}/\ell) for any constant ϵ>0\epsilon > 0 was later given (W., FOCS'11) which is an improvement for non-sparse graphs. We give three new algorithms. The first has the same separator size and running time O(\mbox{poly}(h)\ell m^{1+\epsilon}). This is a significant improvement for small hh and \ell. If =Ω(nϵ)\ell = \Omega(n^{\epsilon'}) for an arbitrarily small chosen constant ϵ>0\epsilon' > 0, we get a time bound of O(\mbox{poly}(h)\ell n^{1+\epsilon}). The second algorithm achieves the same separator size (with a slightly larger polynomial dependency on hh) and running time O(\mbox{poly}(h)(\sqrt\ell n^{1+\epsilon} + n^{2+\epsilon}/\ell^{3/2})) when =Ω(nϵ)\ell = \Omega(n^{\epsilon'}). Our third algorithm has running time O(\mbox{poly}(h)\sqrt\ell n^{1+\epsilon}) when =Ω(nϵ)\ell = \Omega(n^{\epsilon'}). It finds a separator of size O(n/\ell) + \tilde O(\mbox{poly}(h)\ell\sqrt n) which is no worse than previous bounds when hh is fixed and =O~(n1/4)\ell = \tilde O(n^{1/4}). A main tool in obtaining our results is a novel application of a decremental approximate distance oracle of Roditty and Zwick.Comment: 16 pages. Full version of the paper that appeared at ICALP'14. Minor fixes regarding the time bounds such that these bounds hold also for non-sparse graph

    Exact Distance Oracles for Planar Graphs with Failing Vertices

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    We consider exact distance oracles for directed weighted planar graphs in the presence of failing vertices. Given a source vertex uu, a target vertex vv and a set XX of kk failed vertices, such an oracle returns the length of a shortest uu-to-vv path that avoids all vertices in XX. We propose oracles that can handle any number kk of failures. More specifically, for a directed weighted planar graph with nn vertices, any constant kk, and for any q[1,n]q \in [1,\sqrt n], we propose an oracle of size O~(nk+3/2q2k+1)\tilde{\mathcal{O}}(\frac{n^{k+3/2}}{q^{2k+1}}) that answers queries in O~(q)\tilde{\mathcal{O}}(q) time. In particular, we show an O~(n)\tilde{\mathcal{O}}(n)-size, O~(n)\tilde{\mathcal{O}}(\sqrt{n})-query-time oracle for any constant kk. This matches, up to polylogarithmic factors, the fastest failure-free distance oracles with nearly linear space. For single vertex failures (k=1k=1), our O~(n5/2q3)\tilde{\mathcal{O}}(\frac{n^{5/2}}{q^3})-size, O~(q)\tilde{\mathcal{O}}(q)-query-time oracle improves over the previously best known tradeoff of Baswana et al. [SODA 2012] by polynomial factors for q=Ω(nt)q = \Omega(n^t), t(1/4,1/2]t \in (1/4,1/2]. For multiple failures, no planarity exploiting results were previously known
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