Intelligent Impairment Aware Routing Algorithm for All-Optical Networks based on Ant Colony Optimization Trained by Particle Swarm Optimization

In this paper, we propose and analyze the performance of an adaptative impairment aware routing algorithm (IA-RWA) for all-optical networks based on a bio-inspired optimization technique, called Ant Colony Optimization (ACO). We propose a novel heuristic to be used by the routing algorithm combining the physical distance and the wavelengths availability of the optical links. These two metrics are weighted in a training stage. The algorithm was trained by another optimization technique based on swarm collective intelligence, called Particle Swarm Optimization (PSO). We show that our IA-RWA algorithm can learn during the training stage and adapts itself to the network conditions, performing equally or even better than the classical routing algorithms.