Cloud computing can be regarded as one of the best solutions to information technology problems. Most of the proposed scheduling algorithms try to minimize the execution time without considering the cost of accessing ...
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ISBN:
(纸本)9781450364744
Cloud computing can be regarded as one of the best solutions to information technology problems. Most of the proposed scheduling algorithms try to minimize the execution time without considering the cost of accessing resources and mainly target environments resembling a community network. However, workflows were executed parallely in this paper to improve scheduling in cloud computing. For this purpose, the imperialist competitive and genetic algorithms were used. According to the simulation, the proposed algorithm produced better results of cost minimization in comparison with other algorithms. Finally, by applying an efficient scheduling process to the virtual machines running on the cloud, a number of parameters including system efficiency, response time and number of migration more than 10% optimized.
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