期刊名称：International Journal of Grid and Distributed Computing
印刷版ISSN：2005-4262
出版年度：2016
卷号：9
期号：6
页码：269-278
DOI：10.14257/ijgdc.2016.9.6.25
出版社：SERSC
摘要：Aiming at the problem of replica selection optimization in cloud storage load balancing technology, a new dynamic selection algorithm based on genetic algorithm(GASA in short ) is proposed. According to the principle of genetic algorithm, the model of dynamic selection strategy based on genetic algorithm is constructed, and then the key steps of the replica selection criteria and genetic algorithm are mapped, and then the optimal solution is obtained by using the probability equation. Lastly. simulation results from cloud test bed. which is based on Optorsim. show that GASA can reduce data access latency and bandwidth consumption. and effectively achieve cloud load balancing between storage nodes and improve the speed of data access.
