G.M.B. Oliveira and S.S.B.V. Vita (Brazil)
Multi-objective Optimization, Genetic Algorithms, NSGA, NSGA-II, Multicast Routes, Quality of Service.
Multicasting routing involves concurrently data transmission from a source to a subset of destination nodes in a computer network. Quality of Service (QoS) intends to guarantee that the end-to-end communication is obtained with the appropriate service level for each application. Several researchers have investigated genetic algorithms-based models for multicast route computation with QoS requirements. The evolutionary models proposed here use multi-objective approaches in a Pareto sense to solve this problem and to deal with the inheriting multiple metrics involved in QoS proposal. Basically, we construct two multicast QoS routing algorithms; the first one based on NSGA (Non-dominated Sorting Genetic Algorithms) and the second one based on NSGA-II. Three different pairs of objectives were evaluated: one is related to cost links and the other to delay links. We also investigated two different crossover processes. The first employs exactly the same strategy used in previous single-objective models, in which there is a need to pre specify a maximum delay constraint. The second gives the same probability to use either delay or cost metrics when a new multicast tree is generated and there is no need to specify a constraint. Results show that the best environment was obtained using NSGA-II and the equal delay/cost probability-based crossover.
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