Multi-Objective Evolutionary Algorithm for Routing in Wireless Mesh Networks
P. Saraswathi1, M. Prabha2
1P. Saraswathi, Assistant Professor, Information Technology, Anna University, Velammal College of Engineering and Technology, Madurai, India.
2M. Prabha, Assistant Professor, Information Technology, Anna University, Velammal College of Engineering and Technology, Madurai, India
Manuscript received on June 25, 2014. | Revised Manuscript received on July 03, 2014. | Manuscript published on July 05, 2014. | PP: 38-41 | Volume-4, Issue-3, July 2014. | Retrieval Number: C2282074314 /2012©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Wireless Mesh Networks are an attractive technology for providing broadband connectivity to mobile clients who are just on the edge of wired networks, and also for building self organized networks in places where wired infrastructures are not available. Routing in Wireless Mesh Networks has multi-objective nonlinear optimization problem with some constraints. This problem has been addressed by considering Quality of Service parameters such as bandwidth, packet loss rates, delay, path capacity and power consumption. Multi-objective evolutionary algorithms can find multiple Pareto optimal solutions in one single run. This paper uses multi-objective evolutionary algorithm based on the Non-dominated Sorting Genetic Algorithm (NSGA), for solving the dynamic shortest path routing problem. Simulation results show that our proposed algorithm can generate well-distributed Pareto optimal solutions.
Keywords: Multi-objective Optimization, Evolutionary Algorithm, NSGA and Routing.