Particle swarm optimization-based DRWA for wavelength continuous WDM optical networks using a novel fitness function

Abstract

Greater demand of bandwidth and network usage flexibility from customers along with new automated means for network resource management has led to the concept of dynamic resource provisioning in WDM optical networks where unlike the traditional static channel assignment process, network resources can be assigned dynamically. This paper examines a novel particle swarm optimization (PSO)-based scheme to solve dynamic routing and wavelength assignment (dynamic RWA) process needed to provision optical channels for wavelength continuous Wavelength Division Multiplexed (WDM) optical network without any wavelength conversion capability. The proposed PSO scheme employs a novel fitness function which is used during quantization of solutions represented by respective particles of the swarm. The proposed fitness function takes into account the normalized path length of the chosen route and the normalized number of free wavelengths available over the whole route, enabling the PSO-based scheme to be self-tuning by minimizing the need to have a dynamic algorithmic parameter ‘α’ needed for better performance in terms of blocking probability of the connection requests. Simulation results show better performance of the proposed PSO scheme employing novel fitness function for solving dynamic RWA problem, not only in terms of connection blocking probability but also route computation time as compared to other evolutionary schemes like genetic algorithms.