Research on Task Scheduling Based on Particle Swarm Optimization Simulated Annealing Algorithm in Hybrid Cloud Environment

In recent years, cloud computing has developed rapidly. Some problems exist in traditional schedule, such as inefficient task management and unreasonable resource allocation. To solve these problems, a particle swarm simulated annealing (PSO-SA) algorithm is proposed, which improves the inertia weight and learning factor, and redefines the adaptability function, thus effectively improving the task management in the hybrid cloud environment, and further improving the rational allocation of resources. The simulation experiments on the number of tasks and resources show that the performance of PSO-SA algorithm is enhanced after optimization.