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A review energy-efficient task scheduling algorithms in cloud computing

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dc.citedby20
dc.contributor.authorAtiewi S.en_US
dc.contributor.authorYussof S.en_US
dc.contributor.authorEzanee M.en_US
dc.contributor.authorAlmiani M.en_US
dc.contributor.authorid53863311500en_US
dc.contributor.authorid16023225600en_US
dc.contributor.authorid16246214600en_US
dc.contributor.authorid57189663325en_US
dc.date.accessioned2023-05-29T06:11:44Z
dc.date.available2023-05-29T06:11:44Z
dc.date.issued2016
dc.descriptionAlgorithms; Energy efficiency; Internet protocols; Multitasking; Network management; Scheduling; Scheduling algorithms; Datacenter; DVFS; Energy efficient; GreenCloud; Task-scheduling; Virtual machines; Virtualizations; Cloud computingen_US
dc.description.abstractCloud computing is a model for delivering information technology services, wherein resources are retrieved from the Internet through web-based tools and applications instead of a direct connection to a server. The capability to provision and release cloud computing resources with minimal management effort or service provider interaction led to the rapid increase of the use of cloud computing. Therefore, balancing cloud computing resources to provide better performance and services to end users is important. Load balancing in cloud computing means balancing three important stages through which a request is processed. The three stages are data center selection, virtual machine scheduling, and task scheduling at a selected data center. User task scheduling plays a significant role in improving the performance of cloud services. This paper presents a review of various energy-efficient task scheduling methods in a cloud environment. A brief analysis of various scheduling parameters considered in these methods is also presented. The results show that the best power-saving percentage level can be achieved by using both DVFS and DNS. � 2016 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo7494108
dc.identifier.doi10.1109/LISAT.2016.7494108
dc.identifier.scopus2-s2.0-84978485819
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84978485819&doi=10.1109%2fLISAT.2016.7494108&partnerID=40&md5=a47432dbde74d2eb90b60a360026d127
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/22705
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceScopus
dc.sourcetitle2016 IEEE Long Island Systems, Applications and Technology Conference, LISAT 2016
dc.titleA review energy-efficient task scheduling algorithms in cloud computingen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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