Hybrid Optimization for Multiobjective Multicast Routing

The multicast routing protocol in Wireless Sensor Networks (WSN) must be energy aware since the nodes are energy constrained due to limited battery life. This gives rise to the need for efficient multicast routing protocol that is able to determine multicast routes which satisfies the quality of service guarantees and at the same time conserves energy. The transmission of real time multimedia services in wireless sensor networks requires optimal multicast routing protocol that satisfies the quality of service guarantees. The design of such protocol can be formulated as a Multiobjective Multicast Routing Problem (MMRP) that attempts to optimize the objectives simultaneously. The proposal provides a novel multiobjective Hybrid evolutionary algorithm based on Ant Colony Optimization (ACO) and particle swarm optimization (PSO) for MMRP problem. The Hybrid protocol attempts to optimize the end-to-end delay and total transmitted power simultaneously to obtain the Pareto-optimal solutions. The simulation results are very promising and show that our algorithm is able to find near optimal solution efficiently.