An Evaluation of Optimizing for FUD in Scheduling for Shared Computing Environments

Art Sedighi, Milton Smith, Yuefen Deng

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Scheduling systems for shared computing environments such as Cloud, Grid and Cluster computing act as the intermediator agent between the participating users with their requests in form of jobs or tasks, and the resources being shared. We will look at nine scheduling systems in this paper, and evaluate how each would be measured against the three optimizing parameters of Fairness, Utilization and Dynamicity (FUD). The variables are independent to each other, but design decisions made to optimize one variable affects the other two variables. We will demonstrate that batch job-based scheduling systems tend to focus on utilization as the means to reduce response time, whereas interactive task-based scheduling systems tend to focus more on dynamicity as the means to deal with rapid changes in the environment.

Original languageEnglish
Title of host publicationProceedings - 2nd IEEE International Conference on Smart Cloud, SmartCloud 2017
EditorsMeikang Qiu
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages258-262
Number of pages5
ISBN (Electronic)9781538636848
DOIs
StatePublished - Nov 22 2017
Event2nd IEEE International Conference on Smart Cloud, SmartCloud 2017 - New York, United States
Duration: Nov 3 2017Nov 5 2017

Publication series

NameProceedings - 2nd IEEE International Conference on Smart Cloud, SmartCloud 2017

Conference

Conference2nd IEEE International Conference on Smart Cloud, SmartCloud 2017
Country/TerritoryUnited States
CityNew York
Period11/3/1711/5/17

Keywords

  • HPC
  • High Performance Computing
  • Scheduling
  • Shared Computing Environments

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