A New Fitness Function for GA-based Dynamic RWA Algorithms in Optical WDM Networks

Abstract

Genetic algorithms (GA) provide an attractive approach to solving the challenging problem of dynamic routing and wavelength assignment (RWA) in optical wavelength division multiplexing (WDM) networks, with the aim of achieving a significantly low blocking probability. However, available GA-based dynamic RWA algorithms were designed mainly for WDM networks with the wavelength continuity constraint, and they cannot be applied directly to WDM networks with wavelength conversion capability. In this paper, we study the dynamic RWA problem in both optical WDM networks without wavelength conversion and in optical WDM networks with sparse wavelength conversion. By introducing a new fitness function, which is based on the combination of the shortest available path (SAP) and least congested path (LCP) schemes, the GA-based dynamic RWA algorithms can be applied to both these networks and achieve a significantly lower blocking probability than the conventional RWA algorithms. This is verified by extensive simulation studies on the ns-2 network simulator.