26,700 research outputs found

    Optimal distance query reconstruction for graphs without long induced cycles

    Full text link
    Let G=(V,E)G=(V,E) be an nn-vertex connected graph of maximum degree Δ\Delta. Given access to VV and an oracle that given two vertices u,vVu,v\in V, returns the shortest path distance between uu and vv, how many queries are needed to reconstruct EE? We give a simple deterministic algorithm to reconstruct trees using ΔnlogΔn+(Δ+2)n\Delta n\log_\Delta n+(\Delta+2)n distance queries and show that even randomised algorithms need to use at least 1100ΔnlogΔn\frac1{100} \Delta n\log_\Delta n queries in expectation. The best previous lower bound was an information-theoretic lower bound of Ω(nlogn/loglogn)\Omega(n\log n/\log \log n). Our lower bound also extends to related query models including distance queries for phylogenetic trees, membership queries for learning partitions and path queries in directed trees. We extend our deterministic algorithm to reconstruct graphs without induced cycles of length at least kk using OΔ,k(nlogn)O_{\Delta,k}(n\log n) queries, which includes various graph classes of interest such as chordal graphs, permutation graphs and AT-free graphs. Since the previously best known randomised algorithm for chordal graphs uses OΔ(nlog2n)O_{\Delta}(n\log^2 n) queries in expectation, we both get rid off the randomness and get the optimal dependency in nn for chordal graphs and various other graph classes. Finally, we build on an algorithm of Kannan, Mathieu, and Zhou [ICALP, 2015] to give a randomised algorithm for reconstructing graphs of treelength kk using OΔ,k(nlog2n)O_{\Delta,k}(n\log^2n) queries in expectation.Comment: 35 page

    Laplacian Dynamics and Multiscale Modular Structure in Networks

    Full text link
    Most methods proposed to uncover communities in complex networks rely on their structural properties. Here we introduce the stability of a network partition, a measure of its quality defined in terms of the statistical properties of a dynamical process taking place on the graph. The time-scale of the process acts as an intrinsic parameter that uncovers community structures at different resolutions. The stability extends and unifies standard notions for community detection: modularity and spectral partitioning can be seen as limiting cases of our dynamic measure. Similarly, recently proposed multi-resolution methods correspond to linearisations of the stability at short times. The connection between community detection and Laplacian dynamics enables us to establish dynamically motivated stability measures linked to distinct null models. We apply our method to find multi-scale partitions for different networks and show that the stability can be computed efficiently for large networks with extended versions of current algorithms.Comment: New discussions on the selection of the most significant scales and the generalisation of stability to directed network

    Edge Partitions of Optimal 22-plane and 33-plane Graphs

    Full text link
    A topological graph is a graph drawn in the plane. A topological graph is kk-plane, k>0k>0, if each edge is crossed at most kk times. We study the problem of partitioning the edges of a kk-plane graph such that each partite set forms a graph with a simpler structure. While this problem has been studied for k=1k=1, we focus on optimal 22-plane and 33-plane graphs, which are 22-plane and 33-plane graphs with maximum density. We prove the following results. (i) It is not possible to partition the edges of a simple optimal 22-plane graph into a 11-plane graph and a forest, while (ii) an edge partition formed by a 11-plane graph and two plane forests always exists and can be computed in linear time. (iii) We describe efficient algorithms to partition the edges of a simple optimal 22-plane graph into a 11-plane graph and a plane graph with maximum vertex degree 1212, or with maximum vertex degree 88 if the optimal 22-plane graph is such that its crossing-free edges form a graph with no separating triangles. (iv) We exhibit an infinite family of simple optimal 22-plane graphs such that in any edge partition composed of a 11-plane graph and a plane graph, the plane graph has maximum vertex degree at least 66 and the 11-plane graph has maximum vertex degree at least 1212. (v) We show that every optimal 33-plane graph whose crossing-free edges form a biconnected graph can be decomposed, in linear time, into a 22-plane graph and two plane forests

    Quantization as histogram segmentation: globally optimal scalar quantizer design in network systems

    Get PDF
    We propose a polynomial-time algorithm for optimal scalar quantizer design on discrete-alphabet sources. Special cases of the proposed approach yield optimal design algorithms for fixed-rate and entropy-constrained scalar quantizers, multi-resolution scalar quantizers, multiple description scalar quantizers, and Wyner-Ziv scalar quantizers. The algorithm guarantees globally optimal solutions for fixed-rate and entropy-constrained scalar quantizers and constrained optima for the other coding scenarios. We derive the algorithm by demonstrating the connection between scalar quantization, histogram segmentation, and the shortest path problem in a certain directed acyclic graph

    Approximating Minimum Cost Connectivity Orientation and Augmentation

    Get PDF
    We investigate problems addressing combined connectivity augmentation and orientations settings. We give a polynomial-time 6-approximation algorithm for finding a minimum cost subgraph of an undirected graph GG that admits an orientation covering a nonnegative crossing GG-supermodular demand function, as defined by Frank. An important example is (k,)(k,\ell)-edge-connectivity, a common generalization of global and rooted edge-connectivity. Our algorithm is based on a non-standard application of the iterative rounding method. We observe that the standard linear program with cut constraints is not amenable and use an alternative linear program with partition and co-partition constraints instead. The proof requires a new type of uncrossing technique on partitions and co-partitions. We also consider the problem setting when the cost of an edge can be different for the two possible orientations. The problem becomes substantially more difficult already for the simpler requirement of kk-edge-connectivity. Khanna, Naor, and Shepherd showed that the integrality gap of the natural linear program is at most 44 when k=1k=1 and conjectured that it is constant for all fixed kk. We disprove this conjecture by showing an Ω(V)\Omega(|V|) integrality gap even when k=2k=2

    Optimal curing policy for epidemic spreading over a community network with heterogeneous population

    Full text link
    The design of an efficient curing policy, able to stem an epidemic process at an affordable cost, has to account for the structure of the population contact network supporting the contagious process. Thus, we tackle the problem of allocating recovery resources among the population, at the lowest cost possible to prevent the epidemic from persisting indefinitely in the network. Specifically, we analyze a susceptible-infected-susceptible epidemic process spreading over a weighted graph, by means of a first-order mean-field approximation. First, we describe the influence of the contact network on the dynamics of the epidemics among a heterogeneous population, that is possibly divided into communities. For the case of a community network, our investigation relies on the graph-theoretical notion of equitable partition; we show that the epidemic threshold, a key measure of the network robustness against epidemic spreading, can be determined using a lower-dimensional dynamical system. Exploiting the computation of the epidemic threshold, we determine a cost-optimal curing policy by solving a convex minimization problem, which possesses a reduced dimension in the case of a community network. Lastly, we consider a two-level optimal curing problem, for which an algorithm is designed with a polynomial time complexity in the network size.Comment: to be published on Journal of Complex Network

    Hypergraphic LP Relaxations for Steiner Trees

    Get PDF
    We investigate hypergraphic LP relaxations for the Steiner tree problem, primarily the partition LP relaxation introduced by Koenemann et al. [Math. Programming, 2009]. Specifically, we are interested in proving upper bounds on the integrality gap of this LP, and studying its relation to other linear relaxations. Our results are the following. Structural results: We extend the technique of uncrossing, usually applied to families of sets, to families of partitions. As a consequence we show that any basic feasible solution to the partition LP formulation has sparse support. Although the number of variables could be exponential, the number of positive variables is at most the number of terminals. Relations with other relaxations: We show the equivalence of the partition LP relaxation with other known hypergraphic relaxations. We also show that these hypergraphic relaxations are equivalent to the well studied bidirected cut relaxation, if the instance is quasibipartite. Integrality gap upper bounds: We show an upper bound of sqrt(3) ~ 1.729 on the integrality gap of these hypergraph relaxations in general graphs. In the special case of uniformly quasibipartite instances, we show an improved upper bound of 73/60 ~ 1.216. By our equivalence theorem, the latter result implies an improved upper bound for the bidirected cut relaxation as well.Comment: Revised full version; a shorter version will appear at IPCO 2010
    corecore