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The Journal of Supercomputing

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01-08-2016

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

Authors: Xiaodao Chen, Yunliang Chen, Albert Y. Zomaya, Rajiv Ranjan, Shiyan Hu

Published in: The Journal of Supercomputing | Issue 8/2016

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Abstract

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.

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Title: CEVP: Cross Entropy based Virtual Machine Placement for Energy Optimization in Clouds
Authors: Xiaodao Chen
Yunliang Chen
Albert Y. Zomaya
Rajiv Ranjan
Shiyan Hu
Publication date: 01-08-2016
Publisher: Springer US
Published in: The Journal of Supercomputing / Issue 8/2016
Print ISSN: 0920-8542
Electronic ISSN: 1573-0484
DOI: https://doi.org/10.1007/s11227-016-1630-1

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