302 research outputs found

    Distance oracles for unweighted graphs: breaking the quadratic barrier with constant additive error

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    Thorup and Zwick, in the seminal paper [Journal of ACM, 52(1), 2005, pp 1-24], showed that a weighted undirected graph on n vertices can be preprocessed in subcubic time to design a data structure which occupies only subquadratic space, and yet, for any pair of vertices, can answer distance query approximately in constant time. The data structure is termed as approximate distance oracle. Subsequently, there has been improvement in their preprocessing time, and presently the best known algorithms [4, 3] achieve expected O(n2) preprocessing time for these oracles. For a class of graphs, these algorithms indeed run in Θ(n2) time. In this paper, we are able to break this quadratic barrier at the expense of introducing a (small) constant additive error for unweighted graphs. In achieving this goal, we have been able to preserve the optimal size-stretch trade offs of the oracles. One of our algorithms can be extended to weighted graphs, where the additive error becomes 2. ωmax(u, υ) - here ωmax(u, υ) is the heaviest edge in the shortest path between vertices u, υ

    A Linear-Size Logarithmic Stretch Path-Reporting Distance Oracle for General Graphs

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    In 2001 Thorup and Zwick devised a distance oracle, which given an nn-vertex undirected graph and a parameter kk, has size O(kn1+1/k)O(k n^{1+1/k}). Upon a query (u,v)(u,v) their oracle constructs a (2k1)(2k-1)-approximate path Π\Pi between uu and vv. The query time of the Thorup-Zwick's oracle is O(k)O(k), and it was subsequently improved to O(1)O(1) by Chechik. A major drawback of the oracle of Thorup and Zwick is that its space is Ω(nlogn)\Omega(n \cdot \log n). Mendel and Naor devised an oracle with space O(n1+1/k)O(n^{1+1/k}) and stretch O(k)O(k), but their oracle can only report distance estimates and not actual paths. In this paper we devise a path-reporting distance oracle with size O(n1+1/k)O(n^{1+1/k}), stretch O(k)O(k) and query time O(nϵ)O(n^\epsilon), for an arbitrarily small ϵ>0\epsilon > 0. In particular, our oracle can provide logarithmic stretch using linear size. Another variant of our oracle has size O(nloglogn)O(n \log\log n), polylogarithmic stretch, and query time O(loglogn)O(\log\log n). For unweighted graphs we devise a distance oracle with multiplicative stretch O(1)O(1), additive stretch O(β(k))O(\beta(k)), for a function β()\beta(\cdot), space O(n1+1/kβ)O(n^{1+1/k} \cdot \beta), and query time O(nϵ)O(n^\epsilon), for an arbitrarily small constant ϵ>0\epsilon >0. The tradeoff between multiplicative stretch and size in these oracles is far below girth conjecture threshold (which is stretch 2k12k-1 and size O(n1+1/k)O(n^{1+1/k})). Breaking the girth conjecture tradeoff is achieved by exhibiting a tradeoff of different nature between additive stretch β(k)\beta(k) and size O(n1+1/k)O(n^{1+1/k}). A similar type of tradeoff was exhibited by a construction of (1+ϵ,β)(1+\epsilon,\beta)-spanners due to Elkin and Peleg. However, so far (1+ϵ,β)(1+\epsilon,\beta)-spanners had no counterpart in the distance oracles' world. An important novel tool that we develop on the way to these results is a {distance-preserving path-reporting oracle}

    Constructing Light Spanners Deterministically in Near-Linear Time

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    Graph spanners are well-studied and widely used both in theory and practice. In a recent breakthrough, Chechik and Wulff-Nilsen [Shiri Chechik and Christian Wulff-Nilsen, 2018] improved the state-of-the-art for light spanners by constructing a (2k-1)(1+epsilon)-spanner with O(n^(1+1/k)) edges and O_epsilon(n^(1/k)) lightness. Soon after, Filtser and Solomon [Arnold Filtser and Shay Solomon, 2016] showed that the classic greedy spanner construction achieves the same bounds. The major drawback of the greedy spanner is its running time of O(mn^(1+1/k)) (which is faster than [Shiri Chechik and Christian Wulff-Nilsen, 2018]). This makes the construction impractical even for graphs of moderate size. Much faster spanner constructions do exist but they only achieve lightness Omega_epsilon(kn^(1/k)), even when randomization is used. The contribution of this paper is deterministic spanner constructions that are fast, and achieve similar bounds as the state-of-the-art slower constructions. Our first result is an O_epsilon(n^(2+1/k+epsilon\u27)) time spanner construction which achieves the state-of-the-art bounds. Our second result is an O_epsilon(m + n log n) time construction of a spanner with (2k-1)(1+epsilon) stretch, O(log k * n^(1+1/k) edges and O_epsilon(log k * n^(1/k)) lightness. This is an exponential improvement in the dependence on k compared to the previous result with such running time. Finally, for the important special case where k=log n, for every constant epsilon>0, we provide an O(m+n^(1+epsilon)) time construction that produces an O(log n)-spanner with O(n) edges and O(1) lightness which is asymptotically optimal. This is the first known sub-quadratic construction of such a spanner for any k = omega(1). To achieve our constructions, we show a novel deterministic incremental approximate distance oracle. Our new oracle is crucial in our construction, as known randomized dynamic oracles require the assumption of a non-adaptive adversary. This is a strong assumption, which has seen recent attention in prolific venues. Our new oracle allows the order of the edge insertions to not be fixed in advance, which is critical as our spanner algorithm chooses which edges to insert based on the answers to distance queries. We believe our new oracle is of independent interest

    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

    Sublinear Distance Labeling

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    A distance labeling scheme labels the nn nodes of a graph with binary strings such that, given the labels of any two nodes, one can determine the distance in the graph between the two nodes by looking only at the labels. A DD-preserving distance labeling scheme only returns precise distances between pairs of nodes that are at distance at least DD from each other. In this paper we consider distance labeling schemes for the classical case of unweighted graphs with both directed and undirected edges. We present a O(nDlog2D)O(\frac{n}{D}\log^2 D) bit DD-preserving distance labeling scheme, improving the previous bound by Bollob\'as et. al. [SIAM J. Discrete Math. 2005]. We also give an almost matching lower bound of Ω(nD)\Omega(\frac{n}{D}). With our DD-preserving distance labeling scheme as a building block, we additionally achieve the following results: 1. We present the first distance labeling scheme of size o(n)o(n) for sparse graphs (and hence bounded degree graphs). This addresses an open problem by Gavoille et. al. [J. Algo. 2004], hereby separating the complexity from distance labeling in general graphs which require Ω(n)\Omega(n) bits, Moon [Proc. of Glasgow Math. Association 1965]. 2. For approximate rr-additive labeling schemes, that return distances within an additive error of rr we show a scheme of size O(nrpolylog(rlogn)logn)O\left ( \frac{n}{r} \cdot\frac{\operatorname{polylog} (r\log n)}{\log n} \right ) for r2r \ge 2. This improves on the current best bound of O(nr)O\left(\frac{n}{r}\right) by Alstrup et. al. [SODA 2016] for sub-polynomial rr, and is a generalization of a result by Gawrychowski et al. [arXiv preprint 2015] who showed this for r=2r=2.Comment: A preliminary version of this paper appeared at ESA'1
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