A Multi-Objective Pareto-Optimal Genetic Algorithm for QoS Multicasting

The increasing demand of real-time multimedia applications in wireless environment requires stringent Quality of Service (QoS) provisioning to the Mobile Hosts (MH). The scenario becomes more complex during group communication from single source to multiple destinations. Fulfilling users demand with respect to delay, jitter, available bandwidth, packet loss rate and cost associated with the communication needs Multi-Objective Optimization (MOO) with QoS satisfaction, is a NP-complete problem. In this paper we propose a multi-objective optimal algorithm to determine a min-cost multicast tree with end-to-end delay, jitter, packet loss rate and blocking probability constraints. The simulation result shows that the proposed algorithm satisfies QoS requirements (like high availability, good load balancing and fault-tolerance) made by the hosts in varying topology and bursty data traffic for multimedia communication networks. The performance of the algorithm for scalability is also highly encouraged.