Routing and wavelength assignment in optical networks using Artificial Bee Colony algorithm

This paper presents an intelligent approach for modelling Routing and wavelength assignment (RWA) problem in wavelength-routed Dense-Wavelength-Division-Multiplexing (DWDM) optical networks. A new idea based on Artificial Bee Colony (ABC) algorithm is introduced for solving RWA problem which is known to be an NP-hard problem. In the proposed ABC-RWA approach every food source represents a possible and feasible candidate lightpath between each original and destination node pair in demand matrix. The positions of food sources are modified by some artificial bees in the population where the aim is to discover the places of food sources. The food source with the highest nectar value seems to be a solution which is evaluated by the fitness function. The proposed approach is evaluated for both path length (propagation delay) and hops count optimization schemes for PAN EUROPEAN and NSFNET test bench optical networks. The performance of ABC based approach is compared with the Genetic Algorithm (GA) model for solving RWA problem under random and heavy load traffic models. Simulation results demonstrate the ability and efficiency of proposed ABC model for solving RWA in real-world optical networks. Furthermore a comparison study approves that ABC is faster than GA to hit RWA global optimization solutions due to less complexity and computational processing.