3 research outputs found

    A Simple Deterministic Distributed MST Algorithm, with Near-Optimal Time and Message Complexities

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    Distributed minimum spanning tree (MST) problem is one of the most central and fundamental problems in distributed graph algorithms. Garay et al. \cite{GKP98,KP98} devised an algorithm with running time O(D+nlogn)O(D + \sqrt{n} \cdot \log^* n), where DD is the hop-diameter of the input nn-vertex mm-edge graph, and with message complexity O(m+n3/2)O(m + n^{3/2}). Peleg and Rubinovich \cite{PR99} showed that the running time of the algorithm of \cite{KP98} is essentially tight, and asked if one can achieve near-optimal running time **together with near-optimal message complexity**. In a recent breakthrough, Pandurangan et al. \cite{PRS16} answered this question in the affirmative, and devised a **randomized** algorithm with time O~(D+n)\tilde{O}(D+ \sqrt{n}) and message complexity O~(m)\tilde{O}(m). They asked if such a simultaneous time- and message-optimality can be achieved by a **deterministic** algorithm. In this paper, building upon the work of \cite{PRS16}, we answer this question in the affirmative, and devise a **deterministic** algorithm that computes MST in time O((D+n)logn)O((D + \sqrt{n}) \cdot \log n), using O(mlogn+nlognlogn)O(m \cdot \log n + n \log n \cdot \log^* n) messages. The polylogarithmic factors in the time and message complexities of our algorithm are significantly smaller than the respective factors in the result of \cite{PRS16}. Also, our algorithm and its analysis are very **simple** and self-contained, as opposed to rather complicated previous sublinear-time algorithms \cite{GKP98,KP98,E04b,PRS16}

    Near-Additive Spanners In Low Polynomial Deterministic CONGEST Time

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    Given parameters α1,β0\alpha\geq 1,\beta\geq 0, a subgraph G=(V,H)G'=(V,H) of an nn-vertex unweighted undirected graph G=(V,E)G=(V,E) is called an (α,β)(\alpha,\beta)-spanner if for every pair u,vVu,v\in V of vertices, dG(u,v)αdG(u,v)+βd_{G'}(u,v)\leq \alpha d_{G}(u,v)+\beta. If β=0\beta=0 the spanner is called a multiplicative α\alpha-spanner, and if α=1+ϵ\alpha = 1+\epsilon, for an arbitrarily small ϵ>0\epsilon>0, the spanner is said to be a near-additive one. Graph spanners are a fundamental and extremely well-studied combinatorial construct, with a multitude of applications in distributed computing and in other areas. Near-additive spanners, introduced in [EP01], preserve large distances much more faithfully than multiplicative spanners. Also, recent lower bounds [AB15] ruled out the existence of arbitrarily sparse purely additive spanners (i.e., spanners with α=1\alpha=1), and therefore near-additive spanners provide the best approximation of distances that one can hope for. Numerous distributed algorithms for constructing sparse near-additive spanners exist. In particular, there are now known efficient randomized algorithms in the CONGEST model that construct such spanners [EN17], and also there are efficient deterministic algorithms in the LOCAL model [DGPV09]. The only known deterministic CONGEST-model algorithm for the problem [Elk01] requires superlinear time in nn. We remedy the situation and devise an efficient deterministic CONGEST-model algorithm for constructing arbitrarily sparse near-additive spanners. The running time of our algorithm is low polynomial, i.e., roughly O(βnρ)O(\beta \cdot n^\rho), where ρ>0\rho > 0 is an arbitrarily small positive constant that affects the additive term β\beta. In general, the parameters of our algorithm and of the resulting spanner are at the same ballpark as the respective parameters of the state-of-the-art randomized algorithm for the problem due to [EN17]

    Ramsey Spanning Trees and their Applications

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    The metric Ramsey problem asks for the largest subset SS of a metric space that can be embedded into an ultrametric (more generally into a Hilbert space) with a given distortion. Study of this problem was motivated as a non-linear version of Dvoretzky theorem. Mendel and Naor 2007 devised the so called Ramsey Partitions to address this problem, and showed the algorithmic applications of their techniques to approximate distance oracles and ranking problems. In this paper we study the natural extension of the metric Ramsey problem to graphs, and introduce the notion of Ramsey Spanning Trees. We ask for the largest subset SVS\subseteq V of a given graph G=(V,E)G=(V,E), such that there exists a spanning tree of GG that has small stretch for SS. Applied iteratively, this provides a small collection of spanning trees, such that each vertex has a tree providing low stretch paths to all other vertices. The union of these trees serves as a special type of spanner, a tree-padding spanner. We use this spanner to devise the first compact stateless routing scheme with O(1)O(1) routing decision time, and labels which are much shorter than in all currently existing schemes. We first revisit the metric Ramsey problem, and provide a new deterministic construction. We prove that for every kk, any nn-point metric space has a subset SS of size at least n11/kn^{1-1/k} which embeds into an ultrametric with distortion 8k8k. This results improves the best previous result of Mendel and Naor that obtained distortion 128k128k and required randomization. In addition, it provides the state-of-the-art deterministic construction of a distance oracle. Building on this result, we prove that for every kk, any nn-vertex graph G=(V,E)G=(V,E) has a subset SS of size at least n11/kn^{1-1/k}, and a spanning tree of GG, that has stretch O(kloglogn)O(k \log \log n) between any point in SS and any point in VV
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