9,133 research outputs found

    Near-linear Time Algorithm for Approximate Minimum Degree Spanning Trees

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    Given a graph G=(V,E)G = (V, E), we wish to compute a spanning tree whose maximum vertex degree, i.e. tree degree, is as small as possible. Computing the exact optimal solution is known to be NP-hard, since it generalizes the Hamiltonian path problem. For the approximation version of this problem, a O~(mn)\tilde{O}(mn) time algorithm that computes a spanning tree of degree at most Δ+1\Delta^* +1 is previously known [F\"urer \& Raghavachari 1994]; here Δ\Delta^* denotes the minimum tree degree of all the spanning trees. In this paper we give the first near-linear time approximation algorithm for this problem. Specifically speaking, we propose an O~(1ϵ7m)\tilde{O}(\frac{1}{\epsilon^7}m) time algorithm that computes a spanning tree with tree degree (1+ϵ)Δ+O(1ϵ2logn)(1+\epsilon)\Delta^* + O(\frac{1}{\epsilon^2}\log n) for any constant ϵ(0,16)\epsilon \in (0,\frac{1}{6}). Thus, when Δ=ω(logn)\Delta^*=\omega(\log n), we can achieve approximate solutions with constant approximate ratio arbitrarily close to 1 in near-linear time.Comment: 17 page

    Multiple-Edge-Fault-Tolerant Approximate Shortest-Path Trees

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    Let GG be an nn-node and mm-edge positively real-weighted undirected graph. For any given integer f1f \ge 1, we study the problem of designing a sparse \emph{f-edge-fault-tolerant} (ff-EFT) σ\sigma{\em -approximate single-source shortest-path tree} (σ\sigma-ASPT), namely a subgraph of GG having as few edges as possible and which, following the failure of a set FF of at most ff edges in GG, contains paths from a fixed source that are stretched at most by a factor of σ\sigma. To this respect, we provide an algorithm that efficiently computes an ff-EFT (2F+1)(2|F|+1)-ASPT of size O(fn)O(f n). Our structure improves on a previous related construction designed for \emph{unweighted} graphs, having the same size but guaranteeing a larger stretch factor of 3(f+1)3(f+1), plus an additive term of (f+1)logn(f+1) \log n. Then, we show how to convert our structure into an efficient ff-EFT \emph{single-source distance oracle} (SSDO), that can be built in O~(fm)\widetilde{O}(f m) time, has size O(fnlog2n)O(fn \log^2 n), and is able to report, after the failure of the edge set FF, in O(F2log2n)O(|F|^2 \log^2 n) time a (2F+1)(2|F|+1)-approximate distance from the source to any node, and a corresponding approximate path in the same amount of time plus the path's size. Such an oracle is obtained by handling another fundamental problem, namely that of updating a \emph{minimum spanning forest} (MSF) of GG after that a \emph{batch} of kk simultaneous edge modifications (i.e., edge insertions, deletions and weight changes) is performed. For this problem, we build in O(mlog3n)O(m \log^3 n) time a \emph{sensitivity} oracle of size O(mlog2n)O(m \log^2 n), that reports in O(k2log2n)O(k^2 \log^2 n) time the (at most 2k2k) edges either exiting from or entering into the MSF. [...]Comment: 16 pages, 4 figure

    Decomposing highly edge-connected graphs into homomorphic copies of a fixed tree

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    The Tree Decomposition Conjecture by Bar\'at and Thomassen states that for every tree TT there exists a natural number k(T)k(T) such that the following holds: If GG is a k(T)k(T)-edge-connected simple graph with size divisible by the size of TT, then GG can be edge-decomposed into subgraphs isomorphic to TT. So far this conjecture has only been verified for paths, stars, and a family of bistars. We prove a weaker version of the Tree Decomposition Conjecture, where we require the subgraphs in the decomposition to be isomorphic to graphs that can be obtained from TT by vertex-identifications. We call such a subgraph a homomorphic copy of TT. This implies the Tree Decomposition Conjecture under the additional constraint that the girth of GG is greater than the diameter of TT. As an application, we verify the Tree Decomposition Conjecture for all trees of diameter at most 4.Comment: 18 page

    A nearly-mlogn time solver for SDD linear systems

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    We present an improved algorithm for solving symmetrically diagonally dominant linear systems. On input of an n×nn\times n symmetric diagonally dominant matrix AA with mm non-zero entries and a vector bb such that Axˉ=bA\bar{x} = b for some (unknown) vector xˉ\bar{x}, our algorithm computes a vector xx such that xxˉA<ϵxˉA||{x}-\bar{x}||_A < \epsilon ||\bar{x}||_A {A||\cdot||_A denotes the A-norm} in time O~(mlognlog(1/ϵ)).{\tilde O}(m\log n \log (1/\epsilon)). The solver utilizes in a standard way a `preconditioning' chain of progressively sparser graphs. To claim the faster running time we make a two-fold improvement in the algorithm for constructing the chain. The new chain exploits previously unknown properties of the graph sparsification algorithm given in [Koutis,Miller,Peng, FOCS 2010], allowing for stronger preconditioning properties. We also present an algorithm of independent interest that constructs nearly-tight low-stretch spanning trees in time O~(mlogn)\tilde{O}(m\log{n}), a factor of O(logn)O(\log{n}) faster than the algorithm in [Abraham,Bartal,Neiman, FOCS 2008]. This speedup directly reflects on the construction time of the preconditioning chain.Comment: to appear in FOCS1
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