Maximum Edge-Disjoint Paths in Planar Graphs with Congestion 2

We study the maximum edge-disjoint path problem (MEDP) in planar graphs. We are given a set of terminal pairs and wish to find a maximum routable subset of demands. That is, a subset of demands that can be connected by edge-disjoint paths. It is well-known that there is an integrality gap of order square root of the number of nodes for this problem even on a grid-like graph, and hence in planar graphs (Garg et al.). In contrast, Chekuri et al. show that for planar graphs, if LP is the optimal solution to the natural linear programming relaxation for MEDP, then there is a subset of size OPT over the logarithm of the number of nodes which is routable with congestion 2. Subsequently they showed that it is possible to get within a constant factor of the optimal solution with congestion 4 instead of 2. We strengthen this latter result to show that a constant approximation is possible also with congestion 2 (and this is tight via the integrality gap grid example). We use a basic framework from work by Chekuri et al. At the heart of their approach is a 2-phase algorithm that selects an Okamura-Seymour instance. Each of their phases incurs a factor 2 congestion. It is possible to reduce one of the phases to have congestion 1. In order to achieve an overall congestion 2, however, the two phases must share capacity more carefully. For the Phase 1 problem, we extract a problem called rooted clustering that appears to be an interesting problem class in itself.