Computer Networks
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IEEE Transactions on Evolutionary Computation
Bandwidth-delay-constrained least-cost multicast routing based on heuristic genetic algorithm
Computer Communications
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
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This paper presents a new traffic engineering multitree-multiobjective multicast routing algorithm (M-MMA). Multitree traffic engineering uses several trees to transmit one multicast demand between a source and a set of destinations. The purpose of the M-MMA is to balance the traffic load and optimize the utilization of the network resources. For the accomplishment of the optimization goal, M-MMA proposes a local optimization procedure that finds solutions that improve the relative amount of information to be transmitted through each tree.The approach of the M-MMA is inspired in the ideas of the well-known Strength Pareto Evolutionary Algorithm (SPEA). It simultaneously optimizes six objective functions: maximum link utilization, total bandwidth consumption, total cost, hops count, average delay and maximum delay. Simulations on several network topologies prove an enhanced performance when compared to previously published results as the Multiobjective Multicast Algorithm (MMA).