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AuthorDabbagh, Mehiar
AuthorHamdaoui, Bechir
AuthorGuizani, Mohsen
AuthorRayes, Ammar
Available date2022-11-10T09:47:25Z
Publication Date2015
Publication Name2015 IEEE Global Communications Conference, GLOBECOM 2015
ResourceScopus
Resource2-s2.0-84964859764
URIhttp://dx.doi.org/10.1109/GLOCOM.2014.7416959
URIhttp://hdl.handle.net/10576/36165
AbstractManaging cloud resources in a way that reduces the consumed energy while also meeting clients demands is a challenging task. In this paper, we propose an energy-aware resource allocation framework that: i) places the submitted tasks (elastic/inelastic) in an energy-efficient way, ii) decides initially how much resources should be assigned to the elastic tasks, and iii) tunes periodically the allocated resources for the currently hosted elastic tasks. This is all done with the aim of reducing the number of ON servers and the time for which servers need to be kept ON allowing them to be turned to sleep early to save energy while meeting all clients demands. Comparative studies conducted on Google traces show the effectiveness of our framework in terms of energy savings and utilization gains. 2015 IEEE.
Languageen
PublisherInstitute of Electrical and Electronics Engineers Inc.
SubjectCloud computing
Convex optimization
Energy efficiency
Resource allocation
VM placement
TitleOnline assignment and placement of cloud task requests with heterogeneous requirements
TypeConference Paper
dc.accessType Abstract Only


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