Accurate QoS-based service selection algorithm for service composition

The most important thing of service composition (SC) is to select optimal candidate service instances compliant with non-functional requirements (e.g. QoS and load balance constraints). Particle swarm optimization (PSO) is known as an effective and efficient algorithm, which is widely used in this process. However, the premature convergence and diversity loss of PSO may result in suboptimal solutions. In this paper, we propose an accurate sub-swarms particle swarm optimization (ASPSO) algorithm which locates optimal solutions by using sub-swarms searching grid cells in which the density of feasible solutions is high. Simulation results demonstrate that the proposed algorithm improves the accuracy of the standard PSO algorithm in service composition.