Abstract
Data centers play a major role in providing versatile service over the cloud, and so the efficient energy consumption of data centers is the popularly sought-after area of research in cloud computing. This paper highlights the prominent existing works in the area of energy-efficient virtual machine consolidation. The key contribution of this paper is a thorough study on the significant works in VM Consolidation for the past ten years and a listing of the effective unique approaches. A meta-analysis on the existing algorithms for detecting overloaded hosts, selecting suitable VM for migration, and the placement of VMs is performed with PlanetLab workload. Results are compared using ten benchmark parameters, and the best existing algorithmic combination for each parameter is identified and listed.
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John, R.R., Grace Mary Kanaga, E. (2022). A Meta-Analysis on the Algorithms for Virtual Machine Consolidation. In: Peter, J.D., Fernandes, S.L., Alavi, A.H. (eds) Disruptive Technologies for Big Data and Cloud Applications. Lecture Notes in Electrical Engineering, vol 905. Springer, Singapore. https://doi.org/10.1007/978-981-19-2177-3_61
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DOI: https://doi.org/10.1007/978-981-19-2177-3_61
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