Structure and complexity of extreme Nash equilibria

We study extreme Nash equilibria in the context of a selfish routing game. Specifically, we assume a collection of n users, each employing a mixed strategy, which is a probability distribution over m parallel identical links, to control the routing of its own assigned traffic. In a Nash equilibrium, each user selfishly routes its traffic on those links that minimize its expected latency cost. The social cost of a Nash equilibrium is the expectation, over all random choices of the users, of the maximum, over all links, latency through a link. We provide substantial evidence for the Fully Mixed Nash Equilibrium Conjecture, which states that the worst Nash equilibrium is the fully mixed Nash equilibrium, where each user chooses each link with positive probability. Specifically, we prove that the Fully Mixed Nash Equilibrium Conjecture is valid for pure Nash equilibria. Furthermore, we show, that under a certain condition, the social cost of any Nash equilibrium is within a factor of 2h(1+ ε) of that of the fully mixed Nash equilibrium, where h is the factor by which the largest user traffic deviates from the average user traffic. This work has been partially supported by the IST Program of the European Union under contract numbers IST-1999-14186 (ALCOM-FT) and IST-2001-33116 (FLAGS), by funds from the Joint Program of Scientific and Technological Collaboration between Greece and Cyprus, and by research funds at University of Cyprus. ∗ Corresponding author. Tel.: +49 5251 60 6724; fax: +49 5251 60 6697. E-mail addresses: [email protected] (M. Gairing), [email protected] (T. Lücking), [email protected] (M. Mavronicolas), [email protected] (B. Monien), [email protected] (P. Spirakis). 0304-3975/$ see front matter © 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.tcs.2005.05.011 134 M. Gairing et al. / Theoretical Computer Science 343 (2005) 133–157 Considering pure Nash equilibria, we provide a PTAS to approximate the best social cost, we give an upper bound on the worst social cost and we show that it is NP-hard to approximate the worst social cost within a multiplicative factor better than 2− 2/(m+ 1). © 2005 Elsevier B.V. All rights reserved.