Abstract
The job scheduling technology is an effective way to achieve resource sharing and to improve computational efficiency. Scheduling problem has been proved to be NP-complete problems, Particle Swarm Optimization (PSO) algorithm has demonstrated outstanding performance in solving such issues. In cognizance of the characteristics of cluster scheduling problem, a schedule strategy based on PSO was designed and implemented. Comparing with backfilling algorithm, PSO algorithm can improve the fairness of jobs better. It can avoid the problem that bigger jobs can't be executed quickly. The speed and accuracy of strategy generation are improved significantly. The experiment results show that the scheduling strategy based on PSO algorithm can increase the utilization of the CPU and reduce average response time significantly.
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