Research on Task Scheduling Based on Particle Swarm and Membrane Computing in Cloud Computing

Abstract

In view of the high scheduling cost and long time in cloud computing task scheduling, this paper proposes a task scheduling algorithm based on particle swarm and membrane computing. First, a scheduling model based on task cost and time is constructed. Second, the particle swarm algorithm is improved as follows: (1) Use chaos algorithm in the population to optimize; (2) Use domain factors to improve inter-individual Interaction; (3) Use a weighting factor to consider the influence of the number of iterations on the solution; (4) Use extreme perturbation to improve particle vitality; (5) Use Levy to improve particle update position. After each iteration, the membrane calculation is used to update the individual. Finally, in the simulation experiment, the algorithm in this paper is compared with the particle swarm algorithm, the improved particle swarm algorithm, and the membrane calculation algorithm. It has better performance in the two indicators of cost and time. The contrast effect.