Genetic evolutionary algorithm for static traffic grooming to SONET over WDM optical networks

Abstract

In recent years, minimization of SONET-ADMs (Synchronous Optical NETwork-Add-Drop Multiplexers) in WDM (Wavelength Division Multiplexing) optical networks has gained a lot of attention in both the research and commercial arenas. This motivates the research presented in this article. The enhanced searching capability of genetic evolutionary algorithm has been exploited for this purpose. The individuals (chromosomes) have been represented by different sequence of the calls in the traffic matrix. A simple algorithm that minimizes the number of required ADMs based on the shortest path and a possible alternate shortest path has been applied. Some good chromosomes based on some intuitive reasoning have been introduced in the initial population to enhance the convergence of the proposed genetic evolutionary algorithm. The distinguished feature of the proposed algorithm is in introducing the catalyst to direct the convergence of genetic evolutionary algorithm towards its solution. However, the catalyst has been kept small enough to be able to bias the solution. To establish the effectiveness of the proposed algorithm, the simulation results are compared with that of presented in literature with same network configuration and traffic matrix.