16 research outputs found
Sweeping graphs with large clique number
AbstractSearching a network for intruders is an interesting and often difficult problem. Sweeping (or edge searching) is one such search model, in which intruders may exist anywhere along an edge. It was conjectured that graphs exist for which the connected sweep number is strictly less than the monotonic connected sweep number. We prove that this is true, and the difference can be arbitrarily large. We also show that the clique number is a lower bound on the sweep number
On the complexity of optimal homotopies
In this article, we provide new structural results and algorithms for the
Homotopy Height problem. In broad terms, this problem quantifies how much a
curve on a surface needs to be stretched to sweep continuously between two
positions. More precisely, given two homotopic curves and
on a combinatorial (say, triangulated) surface, we investigate the problem of
computing a homotopy between and where the length of the
longest intermediate curve is minimized. Such optimal homotopies are relevant
for a wide range of purposes, from very theoretical questions in quantitative
homotopy theory to more practical applications such as similarity measures on
meshes and graph searching problems.
We prove that Homotopy Height is in the complexity class NP, and the
corresponding exponential algorithm is the best one known for this problem.
This result builds on a structural theorem on monotonicity of optimal
homotopies, which is proved in a companion paper. Then we show that this
problem encompasses the Homotopic Fr\'echet distance problem which we therefore
also establish to be in NP, answering a question which has previously been
considered in several different settings. We also provide an O(log
n)-approximation algorithm for Homotopy Height on surfaces by adapting an
earlier algorithm of Har-Peled, Nayyeri, Salvatipour and Sidiropoulos in the
planar setting
From Pathwidth to Connected Pathwidth
It is proven that the connected pathwidth of any graph is at most
2\cdot\pw(G)+1, where \pw(G) is the pathwidth of . The method is
constructive, i.e. it yields an efficient algorithm that for a given path
decomposition of width computes a connected path decomposition of width at
most . The running time of the algorithm is , where is the
number of `bags' in the input path decomposition.
The motivation for studying connected path decompositions comes from the
connection between the pathwidth and the search number of a graph. One of the
advantages of the above bound for connected pathwidth is an inequality
\csn(G)\leq 2\sn(G)+3, where \csn(G) and \sn(G) are the connected search
number and the search number of . Moreover, the algorithm presented in this
work can be used to convert a given search strategy using searchers into a
(monotone) connected one using searchers and starting at an arbitrary
homebase
Recontamination Helps a Lot to Hunt a Rabbit
The Hunters and Rabbit game is played on a graph G where the Hunter player shoots at k vertices in every round while the Rabbit player occupies an unknown vertex and, if it is not shot, must move to a neighbouring vertex after each round. The Rabbit player wins if it can ensure that its position is never shot. The Hunter player wins otherwise. The hunter number h(G) of a graph G is the minimum integer k such that the Hunter player has a winning strategy (i.e., allowing him to win whatever be the strategy of the Rabbit player). This game has been studied in several graph classes, in particular in bipartite graphs (grids, trees, hypercubes...), but the computational complexity of computing h(G) remains open in general graphs and even in more restricted graph classes such as trees. To progress further in this study, we propose a notion of monotonicity (a well-studied and useful property in classical pursuit-evasion games such as Graph Searching games) for the Hunters and Rabbit game imposing that, roughly, a vertex that has already been shot "must not host the rabbit anymore". This allows us to obtain new results in various graph classes.
More precisely, let the monotone hunter number mh(G) of a graph G be the minimum integer k such that the Hunter player has a monotone winning strategy. We show that pw(G) ? mh(G) ? pw(G)+1 for any graph G with pathwidth pw(G), which implies that computing mh(G), or even approximating mh(G) up to an additive constant, is NP-hard. Then, we show that mh(G) can be computed in polynomial time in split graphs, interval graphs, cographs and trees. These results go through structural characterisations which allow us to relate the monotone hunter number with the pathwidth in some of these graph classes. In all cases, this allows us to specify the hunter number or to show that there may be an arbitrary gap between h and mh, i.e., that monotonicity does not help. In particular, we show that, for every k ? 3, there exists a tree T with h(T) = 2 and mh(T) = k. We conclude by proving that computing h (resp., mh) is FPT parameterised by the minimum size of a vertex cover
Connected searching of weighted trees
AbstractIn this paper we consider the problem of connected edge searching of weighted trees. Barrière et al. claim in [L. Barrière, P. Flocchini, P. Fraigniaud, N. Santoro, Capture of an intruder by mobile agents, in: SPAA’02: Proceedings of the Fourteenth Annual ACM Symposium on Parallel Algorithms and Architectures, ACM, New York, NY, USA, 2002, pp. 200–209] that there exists a polynomial-time algorithm for finding an optimal search strategy, that is, a strategy that minimizes the number of used searchers. However, due to some flaws in their algorithm, the problem turns out to be open. It is proven in this paper that the considered problem is strongly NP-complete even for node-weighted trees (the weight of each edge is 1) with one vertex of degree greater than 2. It is also shown that there exists a polynomial-time algorithm for finding an optimal connected search strategy for a given bounded degree tree with arbitrary weights on the edges and on the vertices. This is an FPT algorithm with respect to the maximum degree of a tree
On the Monotonicity of Process Number
International audienceGraph searching games involve a team of searchers that aims at capturing a fugitive in a graph. These games have been widely studied for their relationships with the tree-and the path-decomposition of graphs. In order to define de-compositions for directed graphs, similar games have been proposed in directed graphs. In this paper, we consider a game that has been defined and studied in the context of routing reconfiguration problems in WDM networks. Namely, in the processing game, the fugitive is invisible, arbitrarily fast, it moves in the opposite direction of the arcs of a digraph, but only as long as it can access to a strongly connected component free of searchers. We prove that the processing game is monotone which leads to its equivalence with a new digraph decomposition