An improved Particle Swarm Optimization Algorithm for QoS-aware Web Service Selection in Service Oriented Communication

QoS-aware Web Service Selection is a crucially important issue in Service Oriented Communication which enables communication by integrating communication web services over Internet. Because of the growing number of candidate web services that provide the same functionality but differ in Quality of Service (QoS), it brings more challenges to select a combination of composite services with optimal QoS performance, while satisfying users’ QoS constraints. Here, an improved Particle Swarm Optimization Algorithm (iPSOA) is proposed to solve this problem. In order to make the algorithm more suitable for QoS-aware Web Service Selection, firstly we redefine the parameters, such as position, velocity and updating operations. In addition, a Non-Uniform Mutation (NUM) strategy is applied to the global best particle to enhance the population diversity on the purpose of overcoming the prematurity of PSOA and a non-uniform mutation function is also designed. Furthermore, the other two contributions are the Adaptive Weight Adjustment (AWA) and Local Best First (LBF) strategies to improve the convergence speed in global and local level respectively. The efficacy of the proposed algorithm for QoS-aware Web Service Selection is illustrated and compared with a modified Genetic Algorithm (GA), QCDSS and PSOA, and the results of experimental evaluation indicate that our approach significantly outperforms the existing methods in execution time with better QoS performance while selecting combinations.