Swarm intelligence based Dynamic Routing and Wavelength Assignment for wavelength constrained all-optical networks

Abstract

This paper examines the problem of Dynamic Routing and Wavelength Assignment (DRWA) in Wavelength Division Multiplexed (WDM) networks with the wavelength continuity constraint applied. Traditional search algorithms like Integer Linear Programming and Graph Colouring become inefficient for solving optimization problems like DRWA because of the complexity of the task. Particle Swarm Optimization (PSO) inspired by swarm intelligence is proposed here to solve DRWA. A novel fitness function is designed for members of the swarm population that takes into account the normalized path length of the chosen route and the normalized number of free wavelengths available over the whole path. This normalization enables the approach to be self-tuning. Simulation results obtained for NSFNET and EON show that the proposed PSO-based scheme achieves a low blocking probability as compared to other swarm intelligence schemes like Genetic Algorithms (GA) for DRWA.