Abstract

In the face of a large number of task requests submitted by users, the data center in the cloud need not only to finish these massive tasks but also to satisfy the user's service demand. How to divide the resources of the system reasonably and schedule these tasks efficiently is a problem that need be solved in the cloud computing. The task scheduling of workflow is a kind of scheduling model for the most part researched in cloud computing. The scheduling goal is always decided by user's QoS (Quality of Service) and the scheduling goal of existing scheduling algorithm is always single. Based on the price model a scheduling algorithm is proposed which can realize the multiple targets in this article, and the scheduling algorithm is Service Cost Optimization based on Particle Swarm Optimization (PSO-SC). PSO-SC algorithm can adapt to dynamic cloud environment, and it not only shortens the completion time of tasks but also minimizes user's cost of task when schedule tasks. In this paper, experiment and analyze the task scheduling of workflow under the cloud computing environment, and the experimental results show that the algorithm proposed in this paper has very good scheduling performance and can reach the goal of task scheduling of tasks.

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