Meta-Heuristic Techniques for Bandwidth Optimization through Dynamic Routing in ATM Networks

Asynchronous Transfer Mode (ATM) is widely used in telecommunications systems to send data, video and voice at a very high speed. ATM based B-ISDN is expected to support varied traffic with varied traffic patterns for dynamic routing for desired network performance. The average cell delay of the entire network is minimized by dynamically routing the traffic. This study proposes a HYBRID approach based on the meta-heuristic optimization techniques using Genetic Algorithm (GA) and Tabu Search (TS) for solving the dynamic routing problem in ATM networks and to optimize the bandwidth. The initialization technique is used to populate the generation to provide an optimal solution at reduced time to avoid premature convergence and efficiency improvement. The algorithm has been coded in the C language.