Virtual Machine Sizing in Virtualized Public Cloud Data Centres

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dc.contributor.authorMosoti Derdus, Kenga
dc.contributor.authorOteke Omwenga, Vincent
dc.contributor.authorOgao, Patrick Job
dc.date.accessioned2022-12-26T11:44:36Z
dc.date.available2022-12-26T11:44:36Z
dc.date.issued2019
dc.description.abstractVirtual machine (VM) consolidation in data centres is a technique that is used to ensure minimum use of physical servers (hosts) leading to better utilization of computing resources and energy savings. To achieve these goals, this technique requires that the estimated VM size is on the basis of application workload resource demands so as to maximize resources utilization, not only at host-level but also at VM-level. This is challenging especially in Infrastructure as a Service (IaaS) public clouds where customers select VM sizes set beforehand by the Cloud Service Providers (CSPs) without the knowledge of the amount of resources their applications need. More often, the resources are overprovisioned and thus go to waste, yet these resources consume power and are paid for by the customers. In this paper, we propose a technique for determining fixed VM sizes, which satisfy application workload resource demands. Because of the dynamic nature of cloud workloads, we show that any resource demands that exceed fixed VM resources can be addressed via statistical multiplexing. The proposed technique is evaluated using VM usage data obtained from a production data centre consisting of 49 hosts and 520 VMs. The evaluations show that the proposed technique reduces energy consumption, memory wastage and CPU wastage by at least 40%, 61% and 41% respectively.en_US
dc.identifier.citationDerdus, K., Omwenga, V., & Ogao, P. (2019). Virtual machine sizing in virtualized public cloud data centres. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 5(4). https://doi.org/10.32628/CSEIT1953124en_US
dc.identifier.urihttps://doi.org/10.32628/CSEIT1953124
dc.identifier.urihttps://nru.uncst.go.ug/handle/123456789/6567
dc.language.isoenen_US
dc.publisherInternational Journal of Scientific Research in Computer Science, Engineering and Information Technologyen_US
dc.subjectVirtual Machines Sizingen_US
dc.subjectVirtual Machine Consolidationen_US
dc.subjectStatistical Multiplexingen_US
dc.titleVirtual Machine Sizing in Virtualized Public Cloud Data Centresen_US
dc.typeArticleen_US
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