• DocumentCode
    719117
  • Title

    An empirical study of most fit, max-min and priority task scheduling algorithms in cloud computing

  • Author

    Taneja, Bhawna

  • Author_Institution
    Dept. of Comput. Sci. & Applic., Kurukshetra Univ., Kurukshetra, India
  • fYear
    2015
  • fDate
    15-16 May 2015
  • Firstpage
    664
  • Lastpage
    667
  • Abstract
    Cloud computing is envisioned to provide each IT enabled service as a utility. From hardware to software, it is committed to fulfill all kind of needs with regard to computation, storage, development etc. at cost-effective and efficient manner. The efficient delivery of services in a cloud largely depends on how it schedules the user jobs (cloudlets) over its resources. A plenty of task scheduling algorithms are available for a cloud provider to choose from. This paper selects three most versatile and fundamental task scheduling algorithms i.e. Most Fit, Max-Min and Priority algorithm to study their comparative performance. From the practical aspect, these algorithms are simulated over cloudsim 3.0.3 toolkit with variable workload circumstances. A set of metrics is also calculated and a comparative assessment of the above mentioned algorithms has been done on the basis of these metrics.
  • Keywords
    cloud computing; minimax techniques; virtual machines; cloud computing; max-min algorithm; most fit algorithm; priority task scheduling algorithm; Cloud computing; Measurement; Quality of service; Resource management; Scheduling; Scheduling algorithms; Cloud Computing Environment; Data; Service Level Agreement; Virtual Machine;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computing, Communication & Automation (ICCCA), 2015 International Conference on
  • Conference_Location
    Noida
  • Print_ISBN
    978-1-4799-8889-1
  • Type

    conf

  • DOI
    10.1109/CCAA.2015.7148457
  • Filename
    7148457