Concepedia

Abstract

In the generalized connectivity problem, we are given an edge-weighted graph G = ( V , E ) and a collection D = {( S 1 , T 1 ), …, ( S k , T k )} of distinct demands each demand ( S i , T i ) is a pair of disjoint vertex subsets. We say that a subgraph F of G connects a demand ( S i , T i ) when it contains a path with one endpoint in S i and the other in T i . The goal is to identify a minimum weight subgraph that connects all demands in D . Alon et al. (SODA '04) introduced this problem to study online network formation settings and showed that it captures some well-studied problems such as Steiner forest, facility location with nonmetric costs, tree multicast, and group Steiner tree. Obtaining a nontrivial approximation ratio for generalized connectivity was left as an open problem. We describe the first poly-logarithmic approximation algorithm for generalized connectivity that has a performance guarantee of O (log 2 n log 2 k ). Here, n is the number of vertices in G and k is the number of demands. We also prove that the cut-covering relaxation of this problem has an O (log 3 n log 2 k ) integrality gap. Building upon the results for generalized connectivity, we obtain improved approximation algorithms for two problems that contain generalized connectivity as a special case. For the directed Steiner network problem, we obtain an O ( k 1/2 + ϵ ) approximation which improves on the currently best performance guarantee of Õ ( k 2/3 ) due to Charikar et al. (SODA '98). For the set connector problem, recently introduced by Fukunaga and Nagamochi (IPCO '07), we present a poly-logarithmic approximation; this result improves on the previously known ratio which can be Ω( n ) in the worst case.

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