Selfish routing and wavelength assignment strategies with advance reservation in inter-domain optical networks

The main challenge in developing large data network in the wide area is in dealing with the scalability of the underlying routing system. Accordingly, in this work we focus on the design of an effective and scalable routing and wavelength assignment (RWA) framework supporting advance reservation services in wavelength-routed WDM networks crossing multiple administrative domains. Our approach is motivated by the observation that traffic in large optical networks spanning several domains is not controlled by a central authority but rather by a large number of independent entities interacting in a distributed manner and aiming at maximizing their own welfare. Due to the selfish strategic behavior of the involved entities, non-cooperative game theory plays an important role in driving our approach. Here the dominant solution concept is the notion of Nash equilibria, which are states of a system in which no participant can gain by deviating unilaterally its strategy. On this concept, we developed a selfish adaptive RWA model supporting advance reservation in large-scale optical wavelength-routed networks and developed a distributed algorithm to compute approximate equilibria in computationally feasible times. We showed how and under which conditions such approach can give rise to a stable state with satisfactory solutions and analyzed its performance and convergence features.