Centroidal localization game
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One important problem in a network is to locate an (invisible) moving entity by using distance-detectors placed at strategical locations. For instance, the metric dimension of a graph G is the minimum number k of detectors placed in some vertices {v_1,...,v_k} such that the vector (d_1,...,d_k) of the distances d(v_i,r) between the detectors and the entity's location r allows to uniquely determine r ∈ V(G). In a more realistic setting, instead of getting the exact distance information, given devices placed in {v_1,...,v_k}, we get only relative distances between the entity's location r and the devices (for every 1≤ i,j≤ k, it is provided whether d(v_i,r) >, <, or = to d(v_j,r)). The centroidal dimension of a graph G is the minimum number of devices required to locate the entity in this setting. We consider the natural generalization of the latter problem, where vertices may be probed sequentially until the moving entity is located. At every turn, a set {v_1,...,v_k} of vertices is probed and then the relative distances between the vertices v_i and the current location r of the entity are given. If not located, the moving entity may move along one edge. Let ζ^* (G) be the minimum k such that the entity is eventually located, whatever it does, in the graph G. We prove that ζ^* (T)≤ 2 for every tree T and give an upper bound on ζ^*(G H) in cartesian product of graphs G and H. Our main result is that ζ^* (G)≤ 3 for any outerplanar graph G. We then prove that ζ^* (G) is bounded by the pathwidth of G plus 1 and that the optimization problem of determining ζ^* (G) is NP-hard in general graphs. Finally, we show that approximating (up to any constant distance) the entity's location in the Euclidean plane requires at most two vertices per turn.
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