An improved ACO based RWA algorithm and its application in wavelength converter allocation issue of the intelligent optical networks

Routing and Wavelength Assignment (RWA) is a key issue in next-generation Intelligent Optical Networks (ION). Considering the Wavelength Continuity Constraint (WCC), RWA algorithms need to introduce the wavelength converter to solve the wavelength conflict due to the limited wavelength resources. A dynamic RWA algorithm based on improved ant colony optimization (ACO) is proposed in this paper. The link idle ratio is introduced into the ant transition probability as a constraint and the random disturbance is added to prevent premature convergence into local optimal path within the less iteration. Theoretical analysis shows that the improved ACO based RWA algorithm can effectively achieve load balancing in optical network. Furthermore, a novel wavelength converter allocation strategy is proposed based on the improved ACO algorithm. The blocking probability and resources utilization through the regular MESH and NSFNET network are compared with numerical simulation, which shows that in the case of the same traffic intensity, the blocking probability and channel utilization performance of the improved algorithm are improved significantly, compared with Dijkstra + First-Fit algorithm with wavelength converters. © 2014 Binary Information Press.