Research on Cloud Computing Task Scheduling Based on Swarm Intelligence Algorithm

As an important research topic in the field of cloud computing, the task scheduling problem has been deeply discussed by the majority of researchers. The overall efficiency of traditional algorithms is low. In the face of the increasing amount of data at present, it is a bit powerless. Aiming at the problem of the completion time in the task scheduling of cloud computing, this paper uses the particle swarm optimization (PSO) and artificial fish swarm algorithm (AFSA) in the swarm intelligence algorithm to fuse and adds three kinds of behavior of artificial fish swarm algorithm in the optimization process of particle swarm algorithm, so that the fusion algorithm (AFPSO) not only retains the characteristics of rapid convergence of particle swarm algorithm but also has the characteristics of artificial fish swarm algorithm which does not always stay in the local best position. Experiments show that the fused algorithm has better performance in task scheduling completion time.