Virtual machine migration algorithm for energy efficiency optimization in cloud computing. (30th August 2018)

• Record Type: Journal Article
• Authors: Zhou, Zhou; Yu, Junyang; Li, Fangmin; Yang, Fei
• Other Names: Laccetti Giuliano guestEditor.; Lapegna Marco guestEditor.; Montella Raffaele guestEditor.; Kosta Sokol guestEditor.; Wu Shaofei guestEditor.
• Is Part Of: Concurrency and computation. Volume 30:Number 24(2018)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2018-08-30
• Subjects: cloud computing -- energy consumption management -- VM migration -- VM selection; Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.4942
• Languages: English
• ISSNs: 1532-0626

Abstract

Summary: Cloud computing has gained more and more attention from industrial and academic circle since it offers pay‐as‐you‐go model, and business applications based on the cloud are also increasing. These applications meet the requirement of users while at the same time triggering the problem of high energy consumption in data centers. To deal with the problem, we propose a new algorithm named EEOM (Energy Efficiency Optimization of VM Migrations). Under considering CPU and memory factors, the key three steps for EEOM algorithm, including trigger time, VM selection, and host location, are optimized. EEOM algorithm takes use of the virtualization technology and migrates some VMs on the lightly loaded host and heavily loaded host to other hosts. The idle hosts are switched to low‐power mode or shut down so as to save energy consumption. The experimental results show that, as compared with Double Threshold (DT) algorithm, the EEOM algorithm saves 7% energy consumption and reduces 13% SLA violations.