985 research outputs found

    Randomized algorithms and upper bounds for multiple domination in graphs and networks

    Get PDF
    We consider four different types of multiple domination and provide new improved upper bounds for the k- and k-tuple domination numbers. They generalize two classical bounds for the domination number and are better than a number of known upper bounds for these two multiple domination parameters. Also, we explicitly present and systematize randomized algorithms for finding multiple dominating sets, whose expected orders satisfy new and recent upper bounds. The algorithms for k- and k-tuple dominating sets are of linear time in terms of the number of edges of the input graph, and they can be implemented as local distributed algorithms. Note that the corresponding multiple domination problems are known to be NP-complete. © 2011 Elsevier B.V. All rights reserved

    k-Tuple_Total_Domination_in_Inflated_Graphs

    Full text link
    The inflated graph GIG_{I} of a graph GG with n(G)n(G) vertices is obtained from GG by replacing every vertex of degree dd of GG by a clique, which is isomorph to the complete graph KdK_{d}, and each edge (xi,xj)(x_{i},x_{j}) of GG is replaced by an edge (u,v)(u,v) in such a way that uXiu\in X_{i}, vXjv\in X_{j}, and two different edges of GG are replaced by non-adjacent edges of GIG_{I}. For integer k1k\geq 1, the kk-tuple total domination number γ×k,t(G)\gamma_{\times k,t}(G) of GG is the minimum cardinality of a kk-tuple total dominating set of GG, which is a set of vertices in GG such that every vertex of GG is adjacent to at least kk vertices in it. For existing this number, must the minimum degree of GG is at least kk. Here, we study the kk-tuple total domination number in inflated graphs when k2k\geq 2. First we prove that n(G)kγ×k,t(GI)n(G)(k+1)1n(G)k\leq \gamma_{\times k,t}(G_{I})\leq n(G)(k+1)-1, and then we characterize graphs GG that the kk-tuple total domination number number of GIG_I is n(G)kn(G)k or n(G)k+1n(G)k+1. Then we find bounds for this number in the inflated graph GIG_I, when GG has a cut-edge ee or cut-vertex vv, in terms on the kk-tuple total domination number of the inflated graphs of the components of GeG-e or vv-components of GvG-v, respectively. Finally, we calculate this number in the inflated graphs that have obtained by some of the known graphs

    Limited packings of closed neighbourhoods in graphs

    Full text link
    The k-limited packing number, Lk(G)L_k(G), of a graph GG, introduced by Gallant, Gunther, Hartnell, and Rall, is the maximum cardinality of a set XX of vertices of GG such that every vertex of GG has at most kk elements of XX in its closed neighbourhood. The main aim in this paper is to prove the best-possible result that if GG is a cubic graph, then L2(G)V(G)/3L_2(G) \geq |V (G)|/3, improving the previous lower bound given by Gallant, \emph{et al.} In addition, we construct an infinite family of graphs to show that lower bounds given by Gagarin and Zverovich are asymptotically best-possible, up to a constant factor, when kk is fixed and Δ(G)\Delta(G) tends to infinity. For Δ(G)\Delta(G) tending to infinity and kk tending to infinity sufficiently quickly, we give an asymptotically best-possible lower bound for Lk(G)L_k(G), improving previous bounds

    Domination parameters with number 2: Interrelations and algorithmic consequences

    Get PDF
    In this paper, we study the most basic domination invariants in graphs, in which number 2 is intrinsic part of their definitions. We classify them upon three criteria, two of which give the following previously studied invariants: the weak 2-domination number, γw2(G), the 2-domination number, γ2(G), the {2}-domination number, γ{2}(G), the double domination number, γ×2(G), the total {2}-domination number, γt{2}(G), and the total double domination number, γt×2(G), where G is a graph in which the corresponding invariant is well defined. The third criterion yields rainbow versions of the mentioned six parameters, one of which has already been well studied, and three other give new interesting parameters. Together with a special, extensively studied Roman domination, γR(G), and two classical parameters, the domination number, γ(G), and the total domination number, γt(G), we consider 13 domination invariants in graphs. In the main result of the paper we present sharp upper and lower bounds of each of the invariants in terms of every other invariant, a large majority of which are new results proven in this paper. As a consequence of the main theorem we obtain new complexity results regarding the existence of approximation algorithms for the studied invariants, matched with tight or almost tight inapproximability bounds, which hold even in the class of split graphs.Fil: Bonomo, Flavia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigación en Ciencias de la Computación. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigación en Ciencias de la Computación; ArgentinaFil: Brešar, Boštjan. Institute of Mathematics, Physics and Mechanics; Eslovenia. University of Maribor; EsloveniaFil: Grippo, Luciano Norberto. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de General Sarmiento. Instituto de Ciencias; ArgentinaFil: Milanič, Martin. University of Primorska; EsloveniaFil: Safe, Martin Dario. Universidad Nacional de General Sarmiento. Instituto de Ciencias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigación en Ciencias de la Computación. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigación en Ciencias de la Computación; Argentin

    Domination parameters with number 2: interrelations and algorithmic consequences

    Full text link
    In this paper, we study the most basic domination invariants in graphs, in which number 2 is intrinsic part of their definitions. We classify them upon three criteria, two of which give the following previously studied invariants: the weak 22-domination number, γw2(G)\gamma_{w2}(G), the 22-domination number, γ2(G)\gamma_2(G), the {2}\{2\}-domination number, γ{2}(G)\gamma_{\{2\}}(G), the double domination number, γ×2(G)\gamma_{\times 2}(G), the total {2}\{2\}-domination number, γt{2}(G)\gamma_{t\{2\}}(G), and the total double domination number, γt×2(G)\gamma_{t\times 2}(G), where GG is a graph in which a corresponding invariant is well defined. The third criterion yields rainbow versions of the mentioned six parameters, one of which has already been well studied, and three other give new interesting parameters. Together with a special, extensively studied Roman domination, γR(G)\gamma_R(G), and two classical parameters, the domination number, γ(G)\gamma(G), and the total domination number, γt(G)\gamma_t(G), we consider 13 domination invariants in graphs GG. In the main result of the paper we present sharp upper and lower bounds of each of the invariants in terms of every other invariant, large majority of which are new results proven in this paper. As a consequence of the main theorem we obtain some complexity results for the studied invariants, in particular regarding the existence of approximation algorithms and inapproximability bounds.Comment: 45 pages, 4 tables, 7 figure

    Deterministic Time-Space Tradeoffs for k-SUM

    Get PDF
    Given a set of numbers, the kk-SUM problem asks for a subset of kk numbers that sums to zero. When the numbers are integers, the time and space complexity of kk-SUM is generally studied in the word-RAM model; when the numbers are reals, the complexity is studied in the real-RAM model, and space is measured by the number of reals held in memory at any point. We present a time and space efficient deterministic self-reduction for the kk-SUM problem which holds for both models, and has many interesting consequences. To illustrate: * 33-SUM is in deterministic time O(n2lglg(n)/lg(n))O(n^2 \lg\lg(n)/\lg(n)) and space O(nlg(n)lglg(n))O\left(\sqrt{\frac{n \lg(n)}{\lg\lg(n)}}\right). In general, any polylogarithmic-time improvement over quadratic time for 33-SUM can be converted into an algorithm with an identical time improvement but low space complexity as well. * 33-SUM is in deterministic time O(n2)O(n^2) and space O(n)O(\sqrt n), derandomizing an algorithm of Wang. * A popular conjecture states that 3-SUM requires n2o(1)n^{2-o(1)} time on the word-RAM. We show that the 3-SUM Conjecture is in fact equivalent to the (seemingly weaker) conjecture that every O(n.51)O(n^{.51})-space algorithm for 33-SUM requires at least n2o(1)n^{2-o(1)} time on the word-RAM. * For k4k \ge 4, kk-SUM is in deterministic O(nk2+2/k)O(n^{k - 2 + 2/k}) time and O(n)O(\sqrt{n}) space

    On general frameworks and threshold functions for multiple domination

    Get PDF
    © 2015 Elsevier B.V. All rights reserved. We consider two general frameworks for multiple domination, which are called (r,s)-domination and parametric domination. They generalise and unify {k}-domination, k-domination, total k-domination and k-tuple domination. In this paper, known upper bounds for the classical domination are generalised for the (r,s)-domination and parametric domination numbers. These generalisations are based on the probabilistic method and they imply new upper bounds for the {k}-domination and total k-domination numbers. Also, we study threshold functions, which impose additional restrictions on the minimum vertex degree, and present new upper bounds for the aforementioned numbers. Those bounds extend similar known results for k-tuple domination and total k-domination
    corecore