Energy efficient virtual machine migration approach with SLA conservation in cloud computing

来源期刊:中南大学学报(英文版)2021年第3期

论文作者:GARG Vaneet JINDAL Balkrishan

文章页码:760 - 770

Key words:cloud computing; energy efficiency; three-gear threshold; resource allocation; service level agreement

Abstract: In the age of online workload explosion, cloud users are increasing exponentialy. Therefore, large scale data centers are required in cloud environment that leads to high energy consumption. Hence, optimal resource utilization is essential to improve energy efficiency of cloud data center. Although, most of the existing literature focuses on virtual machine (VM) consolidation for increasing energy efficiency at the cost of service level agreement degradation. In order to improve the existing approaches, load aware three-gear THReshold (LATHR) as well as modified best fit decreasing (MBFD) algorithm is proposed for minimizing total energy consumption while improving the quality of service in terms of SLA. It offers promising results under dynamic workload and variable number of VMs (1-290) allocated on individual host. The outcomes of the proposed work are measured in terms of SLA, energy consumption, instruction energy ratio (IER) and the number of migrations against the varied numbers of VMs. From experimental results it has been concluded that the proposed technique reduced the SLA violations (55%, 26% and 39%) and energy consumption (17%, 12% and 6%) as compared to median absolute deviation (MAD), inter quartile range (IQR) and double threshold (THR) overload detection policies, respectively.

Cite this article as: GARG Vaneet, JINDAL Balkrishan. Energy efficient virtual machine migration approach with SLA conservation in cloud computing [J]. Journal of Central South University, 2021, 28(3): 760-770. DOI: https://doi.org/10.1007/s11771-021-4643-8.

有色金属在线官网  |   会议  |   在线投稿  |   购买纸书  |   科技图书馆

中南大学出版社 技术支持 版权声明   电话:0731-88830515 88830516   传真:0731-88710482   Email:administrator@cnnmol.com

互联网出版许可证:(署)网出证(京)字第342号   京ICP备17050991号-6      京公网安备11010802042557号