Revising Max-min for Scheduling in a Cloud Computing Context
Moggridge, Paul; Helian, Na; Sun, Yi; Lilley, Mariana; Veneziano, Vito; Eaves, Martin
Citation: Moggridge , P , Helian , N , Sun , Y , Lilley , M , Veneziano , V & Eaves , M 2017 , ' Revising Max-min for Scheduling in a Cloud Computing Context ' Paper presented at The 26th IEEE International Cnference on Enable Technologies: Infrastructure for Collaborative Enerprises , Poznan , Poland , 21/06/17 - 23/06/17 , . DOI: 10.1109/WETICE.2017.58
Adoption of Cloud Computing is on the rise and many datacenter operators adhere to strict energy efficiency guidelines. 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” 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.
Paper 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.
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