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AuthorDabbagh, Mehiar
AuthorHamdaoui, Bechir
AuthorGuizani, Mohsen
AuthorRayes, Ammar
Available date2022-11-10T09:47:22Z
Publication Date2018
Publication NameIEEE Transactions on Emerging Topics in Computing
ResourceScopus
Resource2-s2.0-85043228818
URIhttp://dx.doi.org/10.1109/TETC.2015.2473675
URIhttp://hdl.handle.net/10576/36128
AbstractThis paper exploits cloud task elasticity and price heterogeneity to propose an online resource management framework that maximizes cloud profits while minimizing energy expenses. This is done by reducing the duration during which servers need to be left on and maximizing the monetary revenues when the charging cost for some of the elastic tasks depends on how fast these tasks complete, while meeting all the resource requirements. Comparative studies conducted using Google data traces show the effectiveness of our proposed framework in terms of improving resource utilization, reducing energy expenses, and increasing cloud profits. 2013 IEEE.
Sponsor1Oregon State University, Corvallis, OR 97331 USA 2Qatar University, Doha 2713, Qatar 3Cisco Systems, San Jose, CA 95134 USA CORRESPONDING AUTHOR: M. GUIZANI (mguizani@ieee.org) This work was made possible by NPRP grant # NPRP 5-319-2-121 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.
Languageen
PublisherIEEE Computer Society
Subjectcloud computing
cloud pricing
energy efficiency
Resource allocation
VM placement
TitleExploiting Task Elasticity and Price Heterogeneity for Maximizing Cloud Computing Profits
TypeArticle
Pagination85-96
Issue Number1
Volume Number6
dc.accessType Abstract Only


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