An optimal local approximation algorithm for max-min linear programs

In a max-min LP, the objective is to maximise subject to Ax 1, Cx 1, and x 0 for nonnegative matrices A and C. We present a local algorithm (constant-time distributed algorithm) for approximating max-min LPs. The approximation ratio of our algorithm is the best possible for any local algorithm; there is a matching unconditional lower bound. Categories and Subject Descriptors C.2.4 [Computer-Communication Networks]: Distrib

• Type: Conference
• Year: 2009
• Where: SPAA
• Authors: Patrik Floréen, Joel Kaasinen, Petteri Kaski, Jukka Suomela
• Keywords: Constant-time Distributed Algorithm, Local Algorithm, Parallel Computing, SPAA 2009, Unconditional Lower Bound