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المؤلفDabbagh, Mehiar
المؤلفHamdaoui, Bechir
المؤلفGuizani, Mohsen
المؤلفRayes, Ammar
تاريخ الإتاحة2022-11-10T09:47:25Z
تاريخ النشر2015
اسم المنشور2015 IEEE Global Communications Conference, GLOBECOM 2015
المصدرScopus
المصدر2-s2.0-84964859764
معرّف المصادر الموحدhttp://dx.doi.org/10.1109/GLOCOM.2014.7416959
معرّف المصادر الموحدhttp://hdl.handle.net/10576/36165
الملخصManaging 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.
اللغةen
الناشرInstitute of Electrical and Electronics Engineers Inc.
الموضوعCloud computing
Convex optimization
Energy efficiency
Resource allocation
VM placement
العنوانOnline assignment and placement of cloud task requests with heterogeneous requirements
النوعConference Paper
dc.accessType Abstract Only


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