Multi-constrained multicast routing improved by hybrid bacteria foraging/particle swarm optimization

Abstract

Many network applications like IPTV, news distribution, online chatting, video conferencing, and online games require multi-constrained multicasting. To solve multicast routing under multiple constraints, it is necessary to generate a multi- cast tree structure that ranges from a source to the destinations with a minimum cost and subject to several constraints. In this paper, PSOhas been embedded with BFO to improve the convergence speed and avoid premature convergence to be used for solving the QoS multicast routing problem. The algorithm pro- posed here generates a set of delay compelled links to each destination present in a multicast group. Then, the bacteria foraging algorithm (BFA) selects the paths to all destinations sensibly from the set of least delay paths to construct a multicast tree. To maintain a fair balance among the intensification and diversification of the algorithm being proposed, we have dynamically tuned the parameters of PSO to meet the global search and BFO, which uses the global search technique of PSO to minimize the delay to generate an optimal solution. The robustness of the algorithm being proposed had been established through a simulation. The efficiency and effectiveness of the algorithm being proposed was validated through a comparison study with other existing meta-heuristic algorithms. This shows that our proposed IBF/PSO algorithm outperforms its competitive algorithms.