464 research outputs found

    Dominating 2-broadcast in graphs: complexity, bounds and extremal graphs

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    Limited dominating broadcasts were proposed as a variant of dominating broadcasts, where the broadcast function is upper bounded. As a natural extension of domination, we consider dominating 2-broadcasts along with the associated parameter, the dominating 2-broadcast number. We prove that computing the dominating 2-broadcast number is a NP-complete problem, but can be achieved in linear time for trees. We also give an upper bound for this parameter, that is tight for graphs as large as desired.Peer ReviewedPostprint (author's final draft

    Distributed Connectivity Decomposition

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    We present time-efficient distributed algorithms for decomposing graphs with large edge or vertex connectivity into multiple spanning or dominating trees, respectively. As their primary applications, these decompositions allow us to achieve information flow with size close to the connectivity by parallelizing it along the trees. More specifically, our distributed decomposition algorithms are as follows: (I) A decomposition of each undirected graph with vertex-connectivity kk into (fractionally) vertex-disjoint weighted dominating trees with total weight Ω(klog⁥n)\Omega(\frac{k}{\log n}), in O~(D+n)\widetilde{O}(D+\sqrt{n}) rounds. (II) A decomposition of each undirected graph with edge-connectivity λ\lambda into (fractionally) edge-disjoint weighted spanning trees with total weight ⌈λ−12⌉(1−Δ)\lceil\frac{\lambda-1}{2}\rceil(1-\varepsilon), in O~(D+nλ)\widetilde{O}(D+\sqrt{n\lambda}) rounds. We also show round complexity lower bounds of Ω~(D+nk)\tilde{\Omega}(D+\sqrt{\frac{n}{k}}) and Ω~(D+nλ)\tilde{\Omega}(D+\sqrt{\frac{n}{\lambda}}) for the above two decompositions, using techniques of [Das Sarma et al., STOC'11]. Moreover, our vertex-connectivity decomposition extends to centralized algorithms and improves the time complexity of [Censor-Hillel et al., SODA'14] from O(n3)O(n^3) to near-optimal O~(m)\tilde{O}(m). As corollaries, we also get distributed oblivious routing broadcast with O(1)O(1)-competitive edge-congestion and O(log⁥n)O(\log n)-competitive vertex-congestion. Furthermore, the vertex connectivity decomposition leads to near-time-optimal O(log⁥n)O(\log n)-approximation of vertex connectivity: centralized O~(m)\widetilde{O}(m) and distributed O~(D+n)\tilde{O}(D+\sqrt{n}). The former moves toward the 1974 conjecture of Aho, Hopcroft, and Ullman postulating an O(m)O(m) centralized exact algorithm while the latter is the first distributed vertex connectivity approximation

    A Faster Distributed Single-Source Shortest Paths Algorithm

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    We devise new algorithms for the single-source shortest paths (SSSP) problem with non-negative edge weights in the CONGEST model of distributed computing. While close-to-optimal solutions, in terms of the number of rounds spent by the algorithm, have recently been developed for computing SSSP approximately, the fastest known exact algorithms are still far away from matching the lower bound of Ω~(n+D) \tilde \Omega (\sqrt{n} + D) rounds by Peleg and Rubinovich [SIAM Journal on Computing 2000], where n n is the number of nodes in the network and D D is its diameter. The state of the art is Elkin's randomized algorithm [STOC 2017] that performs O~(n2/3D1/3+n5/6) \tilde O(n^{2/3} D^{1/3} + n^{5/6}) rounds. We significantly improve upon this upper bound with our two new randomized algorithms for polynomially bounded integer edge weights, the first performing O~(nD) \tilde O (\sqrt{n D}) rounds and the second performing O~(nD1/4+n3/5+D) \tilde O (\sqrt{n} D^{1/4} + n^{3/5} + D) rounds. Our bounds also compare favorably to the independent result by Ghaffari and Li [STOC 2018]. As side results, we obtain a (1+ϔ) (1 + \epsilon) -approximation O~((nD1/4+D)/ϔ) \tilde O ((\sqrt{n} D^{1/4} + D) / \epsilon) -round algorithm for directed SSSP and a new work/depth trade-off for exact SSSP on directed graphs in the PRAM model.Comment: Presented at the the 59th Annual IEEE Symposium on Foundations of Computer Science (FOCS 2018

    Dominating 2- broadcast in graphs: complexity, bounds and extremal graphs

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    Limited dominating broadcasts were proposed as a variant of dominating broadcasts, where the broadcast function is upper bounded. As a natural extension of domination, we consider dominating 2-broadcasts along with the associated parameter, the dominating 2-broadcast number. We prove that computing the dominating 2-broadcast number is a NP-complete problem, but can be achieved in linear time for trees. We also give an upper bound for this parameter, that is tight for graphs as large as desiredPostprint (published version

    On (t,r) Broadcast Domination Numbers of Grids

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    The domination number of a graph G=(V,E)G = (V,E) is the minimum cardinality of any subset S⊂VS \subset V such that every vertex in VV is in SS or adjacent to an element of SS. Finding the domination numbers of mm by nn grids was an open problem for nearly 30 years and was finally solved in 2011 by Goncalves, Pinlou, Rao, and Thomass\'e. Many variants of domination number on graphs have been defined and studied, but exact values have not yet been obtained for grids. We will define a family of domination theories parameterized by pairs of positive integers (t,r)(t,r) where 1≀r≀t1 \leq r \leq t which generalize domination and distance domination theories for graphs. We call these domination numbers the (t,r)(t,r) broadcast domination numbers. We give the exact values of (t,r)(t,r) broadcast domination numbers for small grids, and we identify upper bounds for the (t,r)(t,r) broadcast domination numbers for large grids and conjecture that these bounds are tight for sufficiently large grids.Comment: 28 pages, 43 figure

    The Homogeneous Broadcast Problem in Narrow and Wide Strips

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    Let PP be a set of nodes in a wireless network, where each node is modeled as a point in the plane, and let s∈Ps\in P be a given source node. Each node pp can transmit information to all other nodes within unit distance, provided pp is activated. The (homogeneous) broadcast problem is to activate a minimum number of nodes such that in the resulting directed communication graph, the source ss can reach any other node. We study the complexity of the regular and the hop-bounded version of the problem (in the latter, ss must be able to reach every node within a specified number of hops), with the restriction that all points lie inside a strip of width ww. We almost completely characterize the complexity of both the regular and the hop-bounded versions as a function of the strip width ww.Comment: 50 pages, WADS 2017 submissio
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