Research on Convergence Model of Diverse Solution Sets Based on Improved QPSO Algorithm

Aiming at the shortcomings of traditional particle swarm optimization (PSO), an improved QPSO algorithm was proposed and applied to cloud computing resource scheduling strategy. First, the resource allocation problem in the cloud environment is modeled. The adaptive mechanism is introduced in the traditional particle swarm optimization algorithm. The inertia weight in QPSO is modified to make it have strong global optimization ability and accelerate its convergence. The proposed method is simulated by experiments. The experimental results show that the proposed method is better. It can quickly find the resource allocation plan of cloud services. This makes the allocation of resources more scientific and efficient.