• DocumentCode
    1911002
  • Title

    A prediction-based real-time scheduling advisor

  • Author

    Dinda, P.A.

  • Author_Institution
    Dept. of Comput. Sci., Northwestern Univ., Evanston, IL, USA
  • fYear
    2001
  • fDate
    15-19 April 2001
  • Abstract
    The real-time scheduling advisor (RTSA) is an entirely user-level system that an application running on a typical shared, unreserved distributed computing environment can turn to for advice on how to schedule its compute-bound soft real-time tasks. Given a list of hosts, a description of the CPU demands of the task, the deadline, and a confidence level, the RTSA will recommend one of the hosts and predict, as a confidence interval, the running time of the task on that host. The RTSA is based on a scalable and extensible shared resource prediction system based on statistical time series analysis. The author first describes how the RTSA builds on this underlying system to provide its service, and then he evaluates its performance using a randomized methodology based on real background workloads, determining the effect of different factors. He also compares it with a random approach and a measurement-based approach.
  • Keywords
    distributed processing; real-time systems; scheduling; software performance evaluation; time series; CPU demands; compute-bound soft real-time tasks; confidence level; deadline; measurement-based approach; performance; prediction-based real-time scheduling advisor; random approach; randomized methodology; shared resource prediction system; shared unreserved distributed computing; statistical time series analysis; user-level system; Application software; Computer science; Delay; Distributed computing; Environmental management; Operating systems; Processor scheduling; Real time systems; Time series analysis; Visualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel and Distributed Processing Symposium., Proceedings International, IPDPS 2002, Abstracts and CD-ROM
  • Conference_Location
    Ft. Lauderdale, FL
  • Print_ISBN
    0-7695-1573-8
  • Type

    conf

  • DOI
    10.1109/IPDPS.2002.1015480
  • Filename
    1015480