Study of Routing and Wavelength Assignment problem and Performance Analysis of Genetic Algorithm for All-Optical Networks

Abstract

All-optical networks uses the concept of wavelength division multiplexing (WDM). The problem of routing and wavelength assignment (RWA) is critically important for increasing the efficiency of wavelength routed All-optical networks. For the given set of connections, the task of setting up lightpaths by routing and assigning a wavelength to each connection is called routing and wavelength allocation problem. In work to date, the problem has been formulated as integer linear programming problem. There are two variations of the problem: static and dynamic, in the static case, the traffic is known where as in dynamic case, connection request arrive in some random fashion. Here we adopt the static view of the problem. We have studied the Genetic Algorithm to solve the RWA problem and also we studied a modified Genetic Algorithm with reference to the basic model. We studied a novel opimization problem formulations that offer the promise of radical improvements over the existing methods. We adopt a static view of the problem and saw new integer- linear programming formulations, which can be addressed with highly efficient linear programming methods and yield optimal or near-optimal RWA policies. All-optical WDM networks are chracterized by multiple metrics (hop-count, cost, delay), but generally routing protocols only optimize one metric, using some variant shortest path algorithm (e.g., the Dijkstra, all-pairs and Bellman-ford algorithms). The multicriteria RWA problem has been solved combining the relevant metrics or objective functions. The performance of RWA algorithms have been studied across the different standard networks. The performance of both the algorithms are studied with respect to the time taken for making routing decision, number of wavelengths required and cost of the requested lightpaths. It has been observed that the modified genetic algorithm performed better than the existing algorithm with respect to the time and cost parameters.