Quality of Service (QoS) Optimization in a Multicast Routing

Abstract

Optimizing the QoS of multicast routing with multiple constraints is a NP-hard problem. Thus, the use of approximate methods is unavoidable. This article proposes to modify Bat Algorithm (BA) to solve such problem. BA is a metaheuristic that has been applied to several issues of various fields and has given good results, which has owned him a good reputation in terms of robustness and performance. Like any metaheuristic, BA can be trapped in a local optimum. In order to avoid such problem, the authors propose to hybridize BA with the quantum principle and introduce the chaotic map in the calculation of parameters leading to more diversification. The authors chose to adopt a quantum representation for the solutions. The approach, named quantum Bat Algorithm with Chaotic Map (CBAQEA), was experimented and compared with other well-known methods. The experimental results reveal the efficiency and the superiority of the proposed algorithm in terms of multicast routing cost with a good trade-off between intensification and diversification without premature convergence compared to other algorithms in the literature.