University of Hertfordshire

Revising Max-min for Scheduling in a Cloud Computing Context

University of Hertfordshire Research Archive

Help | UH Research Archive

Show simple item record

contributor authorMoggridge, Paul
contributor authorHelian, Na
contributor authorSun, Yi
contributor authorLilley, Mariana
contributor authorVeneziano, Vito
contributor authorEaves, Martin
date accessioned2017-11-14T18:08:17Z
date available2017-11-14T18:08:17Z
date issued2017-08-18
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.2017.58en
identifier citationconferenceen
identifier isbn978-1-5386-1760-1
identifier isbn978-1-5386-1759-5
identifier otherPURE: 13314831
identifier otherPURE UUID: c1f49efa-c0ef-46d1-8ebb-76411b55d5f7
identifier otherScopus: 85034246370
identifier urihttp://hdl.handle.net/2299/19523
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.en
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
language isoeng
publisherIEE
relation ispartof2017 IEEE 26th International Conference on Enabling Technologies:en
rightsen
subjectCloud Computingen
subjectSchedulingen
subjectMax-minen
titleRevising Max-min for Scheduling in a Cloud Computing Contexten
contributor institutionSchool of Computer Scienceen
contributor institutionCentre for Computer Science and Informatics Researchen
identifier doihttps://doi.org/10.1109/WETICE.2017.58
description versionauthorsversionen


This item appears in the following Collection(s)

Show simple item record

Your requested file is now available for download. You may start your download by selecting the following link: test