Abstract
The application characteristics of power industry are very consistent with the technology mode of cloud computing. Task and resource scheduling is one of the basic problems in the cloud computing environment. It is a big challenge to find the optimal solution in a limited time because of the large solution search space. To meet the need of the higher requirements for quality of service and response in the power trading cloud computing platform, a resource scheduling method is proposed based on Improved Particle Swarm Optimization (PSO) algorithm. Firstly, weight of particle is optimized. And then dual fitness function for particle selection strategy is proposed not only aiming at minimum completion time, but also considering quality of computing measurement. Simulation experiments show that the algorithm has a significant improvement in task completion time and resource usage.
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