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Dynamic Task Scheduling Via Policy Iteration Scheduling Approach for Cloud Computing

  • Hu, Bin (School of Computer and Communication Engineering, University of Science and Technology Beijing) ;
  • Xie, Ning (School of Software Engineering,Tongji University) ;
  • Zhao, Tingting (Department of Computer Science and Technology,Tianjin University of Science and Technology) ;
  • Zhang, Xiaotong (School of Computer and Communication Engineering, University of Science and Technology Beijing)
  • Received : 2016.03.03
  • Accepted : 2016.09.18
  • Published : 2017.03.31

Abstract

Dynamic task scheduling is one of the most popular research topics in the cloud computing field. The cloud scheduler dynamically provides VM resources to variable cloud tasks with different scheduling strategies in cloud computing. In this study, we utilized a valid model to describe the dynamic changes of both computing facilities (such as hardware updating) and request task queuing. We built a novel approach called Policy Iteration Scheduling (PIS) to globally optimize the independent task scheduling scheme and minimize the total execution time of priority tasks. We performed experiments with randomly generated cloud task sets and varied the performance of VM resources using Poisson distributions. The results show that PIS outperforms other popular schedulers in a typical cloud computing environment.

Keywords

References

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