文章基本信息

标题：A Data-Placement Strategy Based on Genetic Algorithm in Cloud Computing
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作者：Qiang Xu * , Zhengquan Xu , Tao Wang
期刊名称：International Journal of Intelligence Science
印刷版ISSN：2163-0283
电子版ISSN：2163-0356
出版年度：2015
卷号：05
期号：03
页码：145-157
DOI：10.4236/ijis.2015.53013
语种：English
出版社：Scientific Research Publishing
摘要：With the development of Computerized Business Application, the amount of data is increasing exponentially. Cloud computing provides high performance computing resources and mass storage resources for massive data processing. In distributed cloud computing systems, data intensive computing can lead to data scheduling between data centers. Reasonable data placement can reduce data scheduling between the data centers effectively, and improve the data acquisition efficiency of users. In this paper, the mathematical model of data scheduling between data centers is built. By means of the global optimization ability of the genetic algorithm, generational evolution produces better approximate solution, and gets the best approximation of the data placement at last. The experimental results show that genetic algorithm can effectively work out the approximate optimal data placement, and minimize data scheduling between data centers.
关键词：Cloud Computing; Data Placement; Genetic Algorithm; Data Scheduling