Soft computing approaches to routing and wavelength assignment in wavelength-routed optical networks

The routing and wavelength assignment (RWA) problem is essential for achieving efficient performance in wavelength-routed optical networks. For a network without wavelength conversion capabilities, the RWA problem consists of selecting an appropriate path and wavelength for each connection request while ensuring that paths that share common links are not assigned the same wavelength. The purpose of this research is to develop efficient adaptive methods for routing and wavelength assignment in wavelength-routed optical networks with dynamic traffic. The proposed methods utilize soft computing techniques including genetic algorithms, fuzzy control theory, simulated annealing, and tabu search. All four algorithms consider the current availability of network resources before making a routing decision. Simulations for each algorithm show that each method outperforms fixed and alternate routing strategies in the NSFnet T1 backbone network (irregular topology) and a 4 x 4 mesh-torus network (regular topology). The fuzzy-controlled algorithm achieved the lowest blocking rates and the shortest running times in most cases.