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Virtual machine migration algorithm for energy efficiency optimization in cloud computing
Author(s) -
Zhou Zhou,
Yu Junyang,
Li Fangmin,
Yang Fei
Publication year - 2018
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.4942
Subject(s) - cloud computing , computer science , virtual machine , host (biology) , virtualization , energy consumption , key (lock) , live migration , efficient energy use , idle , distributed computing , energy (signal processing) , algorithm , operating system , real time computing , engineering , ecology , statistics , mathematics , electrical engineering , biology
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.