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AuthorDabbagh, Mehiar
AuthorHamdaoui, Bechir
AuthorGuizani, Mohsen
AuthorRayes, Ammar
Available date2022-11-10T09:47:23Z
Publication Date2015
Publication NameIEEE Transactions on Network and Service Management
ResourceScopus
Resource2-s2.0-84959479991
URIhttp://dx.doi.org/10.1109/TNSM.2015.2436408
URIhttp://hdl.handle.net/10576/36141
AbstractEnergy efficiency has recently become a major issue in large data centers due to financial and environmental concerns. This paper proposes an integrated energy-Aware resource provisioning framework for cloud data centers. The proposed framework: i) predicts the number of virtual machine (VM) requests, to be arriving at cloud data centers in the near future, along with the amount of CPU and memory resources associated with each of these requests, ii) provides accurate estimations of the number of physical machines (PMs) that cloud data centers need in order to serve their clients, and iii) reduces energy consumption of cloud data centers by putting to sleep unneeded PMs. Our framework is evaluated using real Google traces collected over a 29-day period from a Google cluster containing over 12,500 PMs. These evaluations show that our proposed energy-Aware resource provisioning framework makes substantial energy savings. 2004-2012 IEEE.
Languageen
PublisherInstitute of Electrical and Electronics Engineers Inc.
SubjectCloud Computing
Data Clustering
Energy Efficiency
Wiener Filtering
Workload Prediction
TitleEnergy-Efficient Resource Allocation and Provisioning Framework for Cloud Data Centers
TypeArticle
Pagination377-391
Issue Number3
Volume Number12
dc.accessType Abstract Only


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