Maximum Betweenness Centrality: Approximability and Tractable Cases

The Maximum Betweenness Centrality problem (MBC) can be defined as follows. Given a graph find a k-element node set C that maximizes the probability of detecting communication between a pair of nodes s and t chosen uniformly at random. It is assumed that the communication between s and t is realized along a shortest s–t path which is, again, selected uniformly at random. The communication is detected if the communication path contains a node of C. Recently, Dolev et al. (2009) showed that MBC is NP-hard and gave a (1−1/e)-approximation using a greedy approach. We provide a reduction of MBC to Maximum Coverage that simplifies the analysis of the algorithm of Dolev et al. considerably. Our reduction allows us to obtain a new algorithm with the same approximation ratio for a (generalized) budgeted version of MBC. We provide tight examples showing that the analyses of both algorithms are best possible. Moreover, we prove that MBC is APX-complete and provide an exact polynomial-time ...

• Type: Journal
• Year: 2010
• Where: CORR
• Authors: Martin Fink, Joachim Spoerhase
• Keywords: Communication, CORR 2010, Dolev Et, Education, Maximum Betweenness Centrality