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        Revising Max-min for Scheduling in a Cloud Computing Context

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        Author
        Moggridge, Paul
        Helian, Na
        Sun, Yi
        Lilley, Mariana
        Veneziano, Vito
        Eaves, Martin
        Attention
        2299/19523
        Abstract
        Adoption 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].
        Publication date
        2017-08-18
        Published in
        2017 IEEE 26th International Conference on Enabling Technologies:
        Published version
        https://doi.org/10.1109/WETICE.2017.58
        Other links
        http://hdl.handle.net/2299/19523
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