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CEVP: Cross Entropy based Virtual Machine Placement for Energy Optimisation in Clouds

Lookup NU author(s): Professor Raj Ranjan


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Big data trends have recently brought unrivalled opportunities to the cloud systems. Numerous virtual machines (VMs) have been widely deployed to enable the on-demand provisioning and pay-as-you-go services for customers. Due to the large complexity of the current cloud systems, promising VM placement algorithm are highly desirable. This paper focuses on the energy efficiency and thermal stability issues of the cloud systems. A Cross Entropy based VM Placement (CEVP) algorithm is proposed to simultaneously minimize the energy cost, total thermal cost and the number of hot spots in the data center. Simulation results indicate that the proposed CEVP algorithm can (1) achieve energy savings of 26.2% on average, (2) efficiently reduce the temperature cost by up to 6.8% and (3) significantly decrease the total number of the hot spots by 60.1% on average in the cloud systems, by comparing to the Ant Colony System-based algorithm.

Publication metadata

Author(s): Chen X, Chen Y, Zomaya AY, Ranjan R, Hu S

Publication type: Article

Publication status: Published

Journal: Journal of Supercomputing

Year: 2016

Volume: 72

Issue: 8

Pages: 3194-3209

Print publication date: 01/08/2016

Online publication date: 06/02/2016

Acceptance date: 01/11/2015

ISSN (print): 0920-8542

ISSN (electronic): 1573-0484

Publisher: Springer


DOI: 10.1007/s11227-016-1630-1


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Funder referenceFunder name
2014M552112China Postdoctoral Science Foundation
61440018National Natural Science Foundation of China
61501411National Natural Science Foundation of China