A Reference-Based Multiobjective Bacteria Foraging Optimization Technique for QoS Multicast Routing

Nowadays multicast services are gaining high popularity in supporting various and continuous media applications over wired and wireless networks. But the desired quality of service for these applications makes multicast routing optimization a NP Hard problem. In this manuscript, we propose a reference-based multiple objective bacteria foraging algorithm that solves multicasting routing problem, based on user's preference. Instead of searching for a preferred solution from the obtained Pareto front, we would rather search for a set of solutions in the desired objective space simultaneously. The algorithm starts with a single-step tree construction method to generate multicast trees as initial bacteria population. The Pareto optimal front generated will comprise of solutions, each of which best suits the user's choice. The multiobjective bacteria foraging optimization algorithm used here is based on the reference-based method, where the user inputs a reference point in the possible region of the problem search space. Hence the Pareto optimal front generated is in the proximity of the given reference point which would help the user in making more feasible and reliable decisions. Simulations have been carried upon various benchmark as well as some random networks to study and analyze the performance of the proposed algorithm with the existing algorithms. The simulation results reveal that our proposed algorithm (RBMOBFO) yields better results in terms of solution quality and convergence speed.