Journal Article10.1002/CPE.4942
Virtual machine migration algorithm for energy efficiency optimization in cloud computing
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TL;DR: Under considering CPU and memory factors, the key three steps for EEOM algorithm, including trigger time, VM selection, and host location, are optimized and show that the algorithm saves 7% energy consumption and reduces 13% SLA violations.
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Abstract: 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.
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