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dc.contributor.authorMoggridge, Paul
dc.contributor.authorHelian, Na
dc.contributor.authorSun, Yi
dc.contributor.authorLilley, Mariana
dc.contributor.authorVeneziano, Vito
dc.contributor.authorEaves, Martin
dc.date.accessioned2017-11-14T18:08:17Z
dc.date.available2017-11-14T18:08:17Z
dc.date.issued2017-08-18
dc.identifier.citationMoggridge , P , Helian , N , Sun , Y , Lilley , M , Veneziano , V & Eaves , M 2017 , Revising Max-min for Scheduling in a Cloud Computing Context . in 2017 IEEE 26th International Conference on Enabling Technologies: : Infrastructure for Collaborative Enterprises (WETICE) . IEE , The 26th IEEE International Cnference on Enable Technologies: Infrastructure for Collaborative Enerprises , Poznan , Poland , 21/06/17 . DOI: 10.1109/WETICE.2017.58
dc.identifier.citationconference
dc.identifier.isbn978-1-5386-1760-1
dc.identifier.isbn978-1-5386-1759-5
dc.identifier.otherPURE: 13314831
dc.identifier.otherPURE UUID: c1f49efa-c0ef-46d1-8ebb-76411b55d5f7
dc.identifier.otherScopus: 85034246370
dc.identifier.urihttp://hdl.handle.net/2299/19523
dc.descriptionPaper presented at the 2017 IEEE 26th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE), Poznan, Poland, 21-23 June 2017. © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
dc.description.abstractAdoption of Cloud Computing is on the rise[1] and many datacenter operators adhere to strict energy efficiency guidelines[2]. In this paper a novel approach to scheduling in a Cloud Computing context is proposed. The algorithm Maxmin Fast Track (MXFT) revises the Max-min algorithm to better support smaller tasks with stricter Service Level Agreements (SLAs), which makes it more relevant to Cloud Computing. MXFT is inspired by queuing in supermarkets, where there is a fast lane for customers with a smaller number of items. The algorithm outperforms Max-min in task execution times and outperforms Min-min in overall makespan. A by-product of investigating this algorithm was the development of simulator called “ScheduleSim”[3] which makes it simpler to prove a scheduling algorithm before committing to a specific scheduling problem in Cloud Computing and therefore might be a useful precursor to experiments using the established simulator CloudSim[4].en
dc.language.isoeng
dc.publisherIEE
dc.relation.ispartof2017 IEEE 26th International Conference on Enabling Technologies:
dc.rights/dk/atira/pure/core/openaccesspermission/open
dc.subjectCloud Computing
dc.subjectScheduling
dc.subjectMax-min
dc.titleRevising Max-min for Scheduling in a Cloud Computing Contexten
dc.contributor.institutionSchool of Computer Science
dc.contributor.institutionCentre for Computer Science and Informatics Research
dc.relation.schoolSchool of Computer Science
dc.description.versiontypeFinal Accepted Version
dcterms.dateAccepted2017-04-04
rioxxterms.versionAM
rioxxterms.versionofrecordhttps://doi.org/10.1109/WETICE.2017.58
herts.preservation.rarelyaccessedtrue
herts.rights.accesstypeopenAccess


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