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Alternative parameterizations of Metric Dimension

Published 27 Apr 2018 in cs.DS | (1804.10670v1)

Abstract: A set of vertices WW in a graph GG is called resolving if for any two distinct x,y∈V(G)x,y\in V(G), there is v∈Wv\in W such that distG(v,x)≠distG(v,y){\rm dist}_G(v,x)\neq{\rm dist}_G(v,y), where distG(u,v){\rm dist}_G(u,v) denotes the length of a shortest path between uu and vv in the graph GG. The metric dimension md(G){\rm md}(G) of GG is the minimum cardinality of a resolving set. The Metric Dimension problem, i.e. deciding whether md(G)≤k{\rm md}(G)\le k, is NP-complete even for interval graphs (Foucaud et al., 2017). We study Metric Dimension (for arbitrary graphs) from the lens of parameterized complexity. The problem parameterized by kk was proved to be W[2]W[2]-hard by Hartung and Nichterlein (2013) and we study the dual parameterization, i.e., the problem of whether md(G)≤n−k,{\rm md}(G)\le n- k, where nn is the order of GG. We prove that the dual parameterization admits (a) a kernel with at most $3k4$ vertices and (b) an algorithm of runtime O<sup>∗(4<sup>k+o(k)).O<sup>*(4<sup>{k+o(k)}). Hartung and Nichterlein (2013) also observed that Metric Dimension is fixed-parameter tractable when parameterized by the vertex cover number vc(G)vc(G) of the input graph. We complement this observation by showing that it does not admit a polynomial kernel even when parameterized by vc(G)+kvc(G) + k. Our reduction also gives evidence for non-existence of polynomial Turing kernels.

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