405 research outputs found

    Optimal Vertex Fault Tolerant Spanners (for fixed stretch)

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    A kk-spanner of a graph GG is a sparse subgraph HH whose shortest path distances match those of GG up to a multiplicative error kk. In this paper we study spanners that are resistant to faults. A subgraph HGH \subseteq G is an ff vertex fault tolerant (VFT) kk-spanner if HFH \setminus F is a kk-spanner of GFG \setminus F for any small set FF of ff vertices that might "fail." One of the main questions in the area is: what is the minimum size of an ff fault tolerant kk-spanner that holds for all nn node graphs (as a function of ff, kk and nn)? This question was first studied in the context of geometric graphs [Levcopoulos et al. STOC '98, Czumaj and Zhao SoCG '03] and has more recently been considered in general undirected graphs [Chechik et al. STOC '09, Dinitz and Krauthgamer PODC '11]. In this paper, we settle the question of the optimal size of a VFT spanner, in the setting where the stretch factor kk is fixed. Specifically, we prove that every (undirected, possibly weighted) nn-node graph GG has a (2k1)(2k-1)-spanner resilient to ff vertex faults with Ok(f11/kn1+1/k)O_k(f^{1 - 1/k} n^{1 + 1/k}) edges, and this is fully optimal (unless the famous Erdos Girth Conjecture is false). Our lower bound even generalizes to imply that no data structure capable of approximating distGF(s,t)dist_{G \setminus F}(s, t) similarly can beat the space usage of our spanner in the worst case. We also consider the edge fault tolerant (EFT) model, defined analogously with edge failures rather than vertex failures. We show that the same spanner upper bound applies in this setting. Our data structure lower bound extends to the case k=2k=2 (and hence we close the EFT problem for 33-approximations), but it falls to Ω(f1/21/(2k)n1+1/k)\Omega(f^{1/2 - 1/(2k)} \cdot n^{1 + 1/k}) for k3k \ge 3. We leave it as an open problem to close this gap.Comment: To appear in SODA 201

    Sparse Fault-Tolerant BFS Trees

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    This paper addresses the problem of designing a sparse {\em fault-tolerant} BFS tree, or {\em FT-BFS tree} for short, namely, a sparse subgraph TT of the given network GG such that subsequent to the failure of a single edge or vertex, the surviving part TT' of TT still contains a BFS spanning tree for (the surviving part of) GG. Our main results are as follows. We present an algorithm that for every nn-vertex graph GG and source node ss constructs a (single edge failure) FT-BFS tree rooted at ss with O(n \cdot \min\{\Depth(s), \sqrt{n}\}) edges, where \Depth(s) is the depth of the BFS tree rooted at ss. This result is complemented by a matching lower bound, showing that there exist nn-vertex graphs with a source node ss for which any edge (or vertex) FT-BFS tree rooted at ss has Ω(n3/2)\Omega(n^{3/2}) edges. We then consider {\em fault-tolerant multi-source BFS trees}, or {\em FT-MBFS trees} for short, aiming to provide (following a failure) a BFS tree rooted at each source sSs\in S for some subset of sources SVS\subseteq V. Again, tight bounds are provided, showing that there exists a poly-time algorithm that for every nn-vertex graph and source set SVS \subseteq V of size σ\sigma constructs a (single failure) FT-MBFS tree T(S)T^*(S) from each source siSs_i \in S, with O(σn3/2)O(\sqrt{\sigma} \cdot n^{3/2}) edges, and on the other hand there exist nn-vertex graphs with source sets SVS \subseteq V of cardinality σ\sigma, on which any FT-MBFS tree from SS has Ω(σn3/2)\Omega(\sqrt{\sigma}\cdot n^{3/2}) edges. Finally, we propose an O(logn)O(\log n) approximation algorithm for constructing FT-BFS and FT-MBFS structures. The latter is complemented by a hardness result stating that there exists no Ω(logn)\Omega(\log n) approximation algorithm for these problems under standard complexity assumptions

    Exact Computation of a Manifold Metric, via Lipschitz Embeddings and Shortest Paths on a Graph

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    Data-sensitive metrics adapt distances locally based the density of data points with the goal of aligning distances and some notion of similarity. In this paper, we give the first exact algorithm for computing a data-sensitive metric called the nearest neighbor metric. In fact, we prove the surprising result that a previously published 33-approximation is an exact algorithm. The nearest neighbor metric can be viewed as a special case of a density-based distance used in machine learning, or it can be seen as an example of a manifold metric. Previous computational research on such metrics despaired of computing exact distances on account of the apparent difficulty of minimizing over all continuous paths between a pair of points. We leverage the exact computation of the nearest neighbor metric to compute sparse spanners and persistent homology. We also explore the behavior of the metric built from point sets drawn from an underlying distribution and consider the more general case of inputs that are finite collections of path-connected compact sets. The main results connect several classical theories such as the conformal change of Riemannian metrics, the theory of positive definite functions of Schoenberg, and screw function theory of Schoenberg and Von Neumann. We develop novel proof techniques based on the combination of screw functions and Lipschitz extensions that may be of independent interest.Comment: 15 page

    Sparse geometric graphs with small dilation

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    Given a set S of n points in R^D, and an integer k such that 0 <= k < n, we show that a geometric graph with vertex set S, at most n - 1 + k edges, maximum degree five, and dilation O(n / (k+1)) can be computed in time O(n log n). For any k, we also construct planar n-point sets for which any geometric graph with n-1+k edges has dilation Omega(n/(k+1)); a slightly weaker statement holds if the points of S are required to be in convex position

    Fault-Tolerant Spanners: Better and Simpler

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    A natural requirement of many distributed structures is fault-tolerance: after some failures, whatever remains from the structure should still be effective for whatever remains from the network. In this paper we examine spanners of general graphs that are tolerant to vertex failures, and significantly improve their dependence on the number of faults rr, for all stretch bounds. For stretch k3k \geq 3 we design a simple transformation that converts every kk-spanner construction with at most f(n)f(n) edges into an rr-fault-tolerant kk-spanner construction with at most O(r3logn)f(2n/r)O(r^3 \log n) \cdot f(2n/r) edges. Applying this to standard greedy spanner constructions gives rr-fault tolerant kk-spanners with O~(r2n1+2k+1)\tilde O(r^{2} n^{1+\frac{2}{k+1}}) edges. The previous construction by Chechik, Langberg, Peleg, and Roddity [STOC 2009] depends similarly on nn but exponentially on rr (approximately like krk^r). For the case k=2k=2 and unit-length edges, an O(rlogn)O(r \log n)-approximation algorithm is known from recent work of Dinitz and Krauthgamer [arXiv 2010], where several spanner results are obtained using a common approach of rounding a natural flow-based linear programming relaxation. Here we use a different (stronger) LP relaxation and improve the approximation ratio to O(logn)O(\log n), which is, notably, independent of the number of faults rr. We further strengthen this bound in terms of the maximum degree by using the \Lovasz Local Lemma. Finally, we show that most of our constructions are inherently local by designing equivalent distributed algorithms in the LOCAL model of distributed computation.Comment: 17 page
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