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Title: Multi-population ant colony algorithm for virtual machine deployment
Authors: Sun, Xuemei
Zhang, Kai
Ma, Maode
Su, Hua
Keywords: Multi-population
Ant Colony Algorithm
Issue Date: 2017
Source: Sun, X., Zhang, K., Ma, M., & Su, H. (2017). Multi-population ant colony algorithm for virtual machine deployment. IEEE Access, 5, 27014-27022.
Series/Report no.: IEEE Access
Abstract: With the recent rapid development of cloud computing technology, how to reduce the costs of a cloud data center effectively has become an important issue. The study on virtual machine deployment mainly aims at deploying virtual machine resources required by users on a physical server rationally and effectively. This paper proposes a multi-population ant colony algorithm to solve problems of virtual machine deployment. With resource wastage and energy consumption as optimization objectives, this algorithm uses multiple ant colonies for the solution and determines strategies for information exchange among ant colonies according to the information entropy of each population to guarantee the balance of its convergence and diversity. The simulation results show that this algorithm has better performance than the single-population ant colony algorithm and can reduce resource wastage and energy consumption effectively for high-demand virtual machine deployment.
DOI: 10.1109/ACCESS.2017.2768665
Rights: © 2017 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission. See for more information.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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