Space-Efficient Approximation Scheme for Maximum Matching in Sparse Graphs

We present a Logspace Approximation Scheme (LSAS), i. e. an approximation algorithm for maximum matching in planar graphs (not necessarily bipartite) that achieves an approximation ratio arbitrarily close to one, using only logarithmic space. This deviates from the well known Baker's approach for approximation in planar graphs by avoiding the use of distance computation - which is not known to be in Logspace. Our algorithm actually works for any "recursively sparse" graph class which contains a linear size matching and also for certain other classes like bounded genus graphs. The scheme is based on an LSAS in bounded degree graphs which are not known to be amenable to Baker's method. We solve the bounded degree case by parallel augmentation of short augmenting paths. Finding a large number of such disjoint paths can, in turn, be reduced to finding a large independent set in a bounded degree graph. The bounded degree assumption allows us to obtain a Logspace algorithm.

Authors

• Samir Datta
• Raghav Kulkarni
• Anish Mukherjee 0001

Keywords

• maximum matching
• approximation scheme
• logspace
• planar graphs