Author(s)

Haiqin Liu

Corresponding Author

Haiqin Liu

Abstract

Cloud computing is designed to integrate resources and to improve resource utilization. In the cloud computing environment, due to the varied and widely distributed resources, dynamic and changeling user demand, how to close automatically and efficiently task scheduling for the user to the appropriate virtual resources become one of the cloud computing data center is facing enormous challenges. To this problem, an ant colony optimization scheduling algorithm is proposed, dynamic adaptive adjusting pheromone volatilization factor, the user's QoS requirements was developed for the resource selection. By Cloud Sim experiment, the results show that the algorithm can improve the global search ability and avoid falling into local optimum prematurely, can improve the algorithm convergence speed and can balance resources load.

Keywords

Cloud computing, Task scheduling, QoS, Dynamic adaptive