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An optimization method for genetic algorithm about scheduling cloud computing resource

Kang Yanfang, Nie Guihua, Ma Mingming


In the face of the cloud data mining services, it is the target to achieve the data processing across the organization and business operations cross-regional at a low cost, in order to meet the requirements of data sharing and timeliness. How to deploy data and schedule tasks reasonably in the way of reducing the throughput cross data center and at the same time shorting the overall completion time. It is difficult to attain dual optimization about the cost and efficiency. Cloud resources distribution strategy is proposed in this paper, including the data layout strategy and task scheduling strategy. In order to reach the dual optimization goal, we use genetic algorithm to reduce the amount of transfer across data centers and short the execution time, and test the effectiveness of the algorithm through the calculating examples.


Cloud computing,Genetic algorithms,Data layout,Task scheduling and optimization.

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