263 research outputs found
Paired-Domination Game Played in Graphs\u3csup\u3e∗\u3c/sup\u3e
In this paper, we continue the study of the domination game in graphs introduced by Brešar, Klavžar, and Rall [SIAM J. Discrete Math. 24 (2010) 979-991]. We study the paired-domination version of the domination game which adds a matching dimension to the game. This game is played on a graph G by two players, named Dominator and Pairer. They alternately take turns choosing vertices of G such that each vertex chosen by Dominator dominates at least one vertex not dominated by the vertices previously chosen, while each vertex chosen by Pairer is a vertex not previously chosen that is a neighbor of the vertex played by Dominator on his previous move. This process eventually produces a paired-dominating set of vertices of G; that is, a dominating set in G that induces a subgraph that contains a perfect matching. Dominator wishes to minimize the number of vertices chosen, while Pairer wishes to maximize it. The game paired-domination number γgpr(G) of G is the number of vertices chosen when Dominator starts the game and both players play optimally. Let G be a graph on n vertices with minimum degree at least 2. We show that γgpr(G) ≤ 45 n, and this bound is tight. Further we show that if G is (C4, C5)-free, then γgpr(G) ≤ 43 n, where a graph is (C4, C5)-free if it has no induced 4-cycle or 5-cycle. If G is 2-connected and bipartite or if G is 2-connected and the sum of every two adjacent vertices in G is at least 5, then we show that γgpr(G) ≤ 34 n
Vertex Sequences in Graphs
We consider a variety of types of vertex sequences, which are defined in terms of a requirement that the next vertex in the sequence must meet. For example, let S = (v1, v2, …, vk ) be a sequence of distinct vertices in a graph G such that every vertex vi in S dominates at least one vertex in V that is not dominated by any of the vertices preceding it in the sequence S. Such a sequence of maximal length is called a dominating sequence since the set {v1, v2, …, vk } must be a dominating set of G. In this paper we survey the literature on dominating and other related sequences, and propose for future study several new types of vertex sequences, which suggest the beginning of a theory of vertex sequences in graphs
k-Efficient Partitions of Graphs
A set S = {u1, u2,..., ut} of vertices of G is an efficient dominating set if every vertex of G is dominated exactly once by the vertices of S. Letting Ui denote the set of vertices dominated by ui, we note that {U1, U2,... Ut} is a partition of the vertex set of G and that each Ui contains the vertex ui and all the vertices at distance 1 from it in G. In this paper, we generalize the concept of efficient domination by considering k-efficient domination partitions of the vertex set of G, where each element of the partition is a set consisting of a vertex ui and all the vertices at distance di from it, where di ∈ {0, 1,..., k}. For any integer k ≥ 0, the k-efficient domination number of G equals the minimum order of a k-efficient partition of G. We determine bounds on the k-efficient domination number for general graphs, and for k ∈ {1, 2}, we give exact values for some graph families. Complexity results are also obtained
Client–Server and Cost Effective Sets in Graphs
For any integer k≥0, a set of vertices S of a graph G=(V,E) is k-cost-effective if for every v∈S,|N(v)∩(V∖S)|≥|N(v)∩S|+k. In this paper we study the minimum cardinality of a maximal k-cost-effective set and the maximum cardinality of a k-cost-effective set. We obtain Gallai-type results involving the k-cost-effective and global k-offensive alliance parameters, and we provide bounds on the maximum k-cost-effective number. Finally, we consider k-cost-effective sets that are also dominating. We show that computing the k-cost-effective domination number is NP-complete for bipartite graphs. Moreover, we note that not all trees have a k-cost-effective dominating set and give a constructive characterization of those that do
Client–server and cost effective sets in graphs
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Maclyn McCarty (1911-2005)
"If I have seen further, it is by standing on the shoulders of giants" (letter of Isaac Newton to Robert Hooke). This well-known sentence of Newton finds its correct meaning in biology through the work of Oswald Avery (1877-1955), Colin MacLeod (1909-1972), and Maclyn McCarty (1911-2005) that was published in 1944 in The Journal of Experimental Medicine, which showed that DNA carried genetic information. These giants of molecular biology attained scientific evidence to provide shoulders strong enough to allow Crick and Watson to build on the foundations laid down by this group to postulate, 9 years later, the double-helix model of DNA. Maclyn McCarty died in New York on January 3, 2005, at age 93. At the time of his death, he was an active editor of the above-mentioned journal, which is published by The Rockefeller University.Peer reviewe
Total domination stable graphs upon edge addition
AbstractA set S of vertices in a graph G is a total dominating set if every vertex of G is adjacent to some vertex in S. The minimum cardinality of a total dominating set of G is the total domination number of G. A graph is total domination edge addition stable if the addition of an arbitrary edge has no effect on the total domination number. In this paper, we characterize total domination edge addition stable graphs. We determine a sharp upper bound on the total domination number of total domination edge addition stable graphs, and we determine which combinations of order and total domination number are attainable. We finish this work with an investigation of claw-free total domination edge addition stable graphs
Powerful alliances in graphs
AbstractFor a graph G=(V,E), a non-empty set S⊆V is a defensive alliance if for every vertex v in S, v has at most one more neighbor in V−S than it has in S, and S is an offensive alliance if for every v∈V−S that has a neighbor in S, v has more neighbors in S than in V−S. A powerful alliance is both defensive and offensive. We initiate the study of powerful alliances in graphs
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