494 research outputs found

    Estimating the weight of metric minimum spanning trees in sublinear time

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    In this paper we present a sublinear-time (1+Īµ)(1+\varepsilon)-approximation randomized algorithm to estimate the weight of the minimum spanning tree of an nn-point metric space. The running time of the algorithm is O~(n/ĪµO(1))\widetilde{\mathcal{O}}(n/\varepsilon^{\mathcal{O}(1)}). Since the full description of an nn-point metric space is of size Ī˜(n2)\Theta(n^2), the complexity of our algorithm is sublinear with respect to the input size. Our algorithm is almost optimal as it is not possible to approximate in o(n)o(n) time the weight of the minimum spanning tree to within any factor. We also show that no deterministic algorithm can achieve a BB-approximation in o(n2/B3)o(n^2/B^3) time. Furthermore, it has been previously shown that no o(n2)o(n^2) algorithm exists that returns a spanning tree whose weight is within a constant times the optimum

    Parallel algorithm for the matrix chain product problem

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    This paper considers the problem of finding an optimal order of the multiplication chain of matrices. All parallel algorithms known use the dynamic programming approach and run in a polylogarithmic time using, in the best case, n6/log6n processors. Our algorithm uses a different approach and reduces the problem to computing some recurrence on a tree. We show that this recurrence can be optimally solved which enables us to improve the parallel bound by a few factors. Our algorithm runs in O (log3n) time using n2/log3n processors on a CREW PRAM and O(log2n log log n) time using n2/(log2n log log n)processors on a CRCW PRAM. This algorithm solves also the problem of finding an optimal triangulation in a convex polygon. We show that for a monotone polygon this result can be even improved to get an O(log2n) time and n processor algorithm on a CREW PRAM

    Exploiting spontaneous transmissions for broadcasting and leader election in radio networks

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    We study two fundamental communication primitives: broadcasting and leader election in the classical model of multi-hop radio networks with unknown topology and without collision detection mechanisms. It has been known for almost 20 years that in undirected networks with n nodes and diameter D, randomized broadcasting requires Ī©(D log n/D + log2 n) rounds, assuming that uninformed nodes are not allowed to communicate (until they are informed). Only very recently, Haeupler and Wajc (PODC'2016) showed that this bound can be improved for the model with spontaneous transmissions, providing an O(D log n log log n/log D + logO(1) n)-time broadcasting algorithm. In this article, we give a new and faster algorithm that completes broadcasting in O(D log n/log D + logO(1) n) time, succeeding with high probability. This yields the first optimal O(D)-time broadcasting algorithm whenever n is polynomial in D. Furthermore, our approach can be applied to design a new leader election algorithm that matches the performance of our broadcasting algorithm. Previously, all fast randomized leader election algorithms have used broadcasting as a subroutine and their complexity has been asymptotically strictly larger than the complexity of broadcasting. In particular, the fastest previously known randomized leader election algorithm of Ghaffari and Haeupler (SODA'2013) requires O(D log n/D min {log log n, log n/D} + logO(1) n)-time, succeeding with high probability. Our new algorithm again requires O(D log n/log D + logO(1) n) time, also succeeding with high probability

    Deterministic Communication in Radio Networks

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    In this paper we improve the deterministic complexity of two fundamental communication primitives in the classical model of ad-hoc radio networks with unknown topology: broadcasting and wake-up. We consider an unknown radio network, in which all nodes have no prior knowledge about network topology, and know only the size of the network nn, the maximum in-degree of any node Ī”\Delta, and the eccentricity of the network DD. For such networks, we first give an algorithm for wake-up, based on the existence of small universal synchronizers. This algorithm runs in O(minā”{n,DĪ”}logā”nlogā”Ī”logā”logā”Ī”)O(\frac{\min\{n, D \Delta\} \log n \log \Delta}{\log\log \Delta}) time, the fastest known in both directed and undirected networks, improving over the previous best O(nlogā”2n)O(n \log^2n)-time result across all ranges of parameters, but particularly when maximum in-degree is small. Next, we introduce a new combinatorial framework of block synchronizers and prove the existence of such objects of low size. Using this framework, we design a new deterministic algorithm for the fundamental problem of broadcasting, running in O(nlogā”Dlogā”logā”DĪ”n)O(n \log D \log\log\frac{D \Delta}{n}) time. This is the fastest known algorithm for the problem in directed networks, improving upon the O(nlogā”nlogā”logā”n)O(n \log n \log \log n)-time algorithm of De Marco (2010) and the O(nlogā”2D)O(n \log^2 D)-time algorithm due to Czumaj and Rytter (2003). It is also the first to come within a log-logarithmic factor of the Ī©(nlogā”D)\Omega(n \log D) lower bound due to Clementi et al.\ (2003). Our results also have direct implications on the fastest \emph{deterministic leader election} and \emph{clock synchronization} algorithms in both directed and undirected radio networks, tasks which are commonly used as building blocks for more complex procedures

    Helly-Type Theorems in Property Testing

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    Helly's theorem is a fundamental result in discrete geometry, describing the ways in which convex sets intersect with each other. If SS is a set of nn points in RdR^d, we say that SS is (k,G)(k,G)-clusterable if it can be partitioned into kk clusters (subsets) such that each cluster can be contained in a translated copy of a geometric object GG. In this paper, as an application of Helly's theorem, by taking a constant size sample from SS, we present a testing algorithm for (k,G)(k,G)-clustering, i.e., to distinguish between two cases: when SS is (k,G)(k,G)-clusterable, and when it is Ļµ\epsilon-far from being (k,G)(k,G)-clusterable. A set SS is Ļµ\epsilon-far (0<Ļµā‰¤1)(0<\epsilon\leq1) from being (k,G)(k,G)-clusterable if at least Ļµn\epsilon n points need to be removed from SS to make it (k,G)(k,G)-clusterable. We solve this problem for k=1k=1 and when GG is a symmetric convex object. For k>1k>1, we solve a weaker version of this problem. Finally, as an application of our testing result, in clustering with outliers, we show that one can find the approximate clusters by querying a constant size sample, with high probability

    Selfish traffic allocation for server farms

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    We study the price of selfish routing in noncooperative networks like the Internet. In particular, we investigate the price of selfish routing using the price of anarchy (a.k.a. the coordination ratio) and other (e.g., bicriteria) measures in the recently introduced game theoretic parallel links network model of Koutsoupias and Papadimitriou. We generalize this model toward general, monotone families of cost functions and cost functions from queueing theory. A summary of our main results for general, monotone cost functions is as follows: 1. We give an exact characterization of all cost functions having a bounded/unbounded price of anarchy. For example, the price of anarchy for cost functions describing the expected delay in queueing systems is unbounded. 2. We show that an unbounded price of anarchy implies an extremely high performance degradation under bicriteria measures. In fact, the price of selfish routing can be as high as a bandwidth degradation by a factor that is linear in the network size. 3. We separate the game theoretic (integral) allocation model from the (fractional) flow model by demonstrating that even a very small or negligible amount of integrality can lead to a dramatic performance degradation. 4. We unify recent results on selfish routing under different objectives by showing that an unbounded price of anarchy under the min-max objective implies an unbounded price of anarchy under the average cost objective and vice versa. Our special focus lies on cost functions describing the behavior of Web servers that can open only a limited number of Transmission Control Protocol (TCP) connections. In particular, we compare the performance of queueing systems that serve all incoming requests with servers that reject requests in case of overload. Our analysis indicates that all queueing systems without rejection cannot give any reasonable guarantee on the expected delay of requests under selfish routing even when the injected load is far away from the capacity of the system. In contrast, Web server farms that are allowed to reject requests can guarantee a high quality of service for every individual request stream even under relatively high injection rates

    Faster Deterministic Communication in Radio Networks

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    In this paper we improve the deterministic complexity of two fundamental communication primitives in the classical model of ad-hoc radio networks with unknown topology: broadcasting and wake-up. We consider an unknown radio network, in which all nodes have no prior knowledge about network topology, and know only the size of the network n, the maximum in-degree of any node Delta, and the eccentricity of the network D. For such networks, we first give an algorithm for wake-up, in both directed and undirected networks, based on the existence of small universal synchronizers. This algorithm runs in O((min{n,D*Delta}*log(n)*log(Delta))/(log(log(Delta)))) time, improving over the previous best O(n*log^2(n))-time result across all ranges of parameters, but particularly when maximum in-degree is small. Next, we introduce a new combinatorial framework of block synchronizers and prove the existence of such objects of low size. Using this framework, we design a new deterministic algorithm for the fundamental problem of broadcasting, running in O(n*log(D)*log(log((D*Delta)/n))) time. This is the fastest known algorithm for this problems, improving upon the O(n*log(n)*log*log(n))-time algorithm of De Marco (2010) and the O(n*log^2(D))-time algorithm due to Czumaj and Rytter (2003), the previous fastest results for directed networks, and is the first to come within a log-logarithmic factor of the Omega(n*log(D)) lower bound due to Clementi et al. (2003). Our results have also direct implications on the fastest deterministic leader election and clock synchronization algorithms in both directed and undirected radio networks, tasks which are commonly used as building blocks for more complex procedures
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