Exclusive Graph Searching - Archive ouverte HAL Access content directly
Conference Papers Year : 2013

Exclusive Graph Searching


This paper tackles the well known graph searching problem, where a team of searchers aims at capturing an intruder in a network, modeled as a graph. All variants of this problem assume that any node can be simultaneously occupied by several searchers. This assumption may be unrealistic, e.g., in the case of searchers modeling physical searchers, or may require each individual node to provide additional resources, e.g., in the case of searchers modeling software agents. We thus investigate exclusive graph searching, in which no two or more searchers can occupy the same node at the same time, and, as for the classical variants of graph searching, we study the minimum number of searchers required to capture the intruder. This number is called the exclusive search number of the considered graph. Exclusive graph searching appears to be considerably more complex than classical graph searching, for at least two reasons: (1) it does not satisfy the monotonicity property, and (2) it is not closed under minor. Nevertheless, we design a polynomial-time algorithm which, given any tree T , computes the exclusive search number of T . Moreover, for any integer k, we provide a characterization of the trees T with exclusive search number at most k. This characterization allows us to describe a special type of exclusive search strategies, that can be executed in a distributed environment, i.e., in a framework in which the searchers are limited to cooperate in a distributed manner.
Fichier principal
Vignette du fichier
paper_201.pdf (303.92 Ko) Télécharger le fichier
Origin Files produced by the author(s)

Dates and versions

hal-00845530 , version 1 (17-07-2013)



Lélia Blin, Janna Burman, Nicolas Nisse. Exclusive Graph Searching. 21st European Symposium on Algorithms (ESA 2013), Sep 2013, Sophia Antipolis, France. pp.181-192, ⟨10.1007/978-3-642-40450-4_16⟩. ⟨hal-00845530⟩
1168 View
478 Download



Gmail Mastodon Facebook X LinkedIn More