• DocumentCode
    2848806
  • Title

    Research on Predictable Scheduling Strategy of Virtual Computing Systems Based on Lookahead

  • Author

    Liu, Shixi ; Xu, Zhicai ; Chen, GuiLin ; Hu, Xiaojing

  • Author_Institution
    Comput. Sci. & Technol. Dept., Chuzhou Univ., Chuzhou, China
  • fYear
    2009
  • fDate
    11-13 Dec. 2009
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Processor scheduling in computer science has been one of the most important research fields, and the scheduling of multiprocessor system is the most important extensively studied in depth. Lookahead computation is an effective method that improves the distributed simulation performance of stochastic petri nets (SPN). It enables us to analyze the structure of nets to reduce the delay time for partitioning the nets blindly. The M/M/n/k model with churn of virtual computing system is given by taking advantage of SPN. The predictable scheduling strategy based on lookahead is presented. The approach based on a part of optimism computed on the prediction time can determine advancement of each user task. The theorem shows that if every task is distributed to virtual machine for running along transmission path with least lookahead, the whole delay time of all tasks in buffer is the shortest.
  • Keywords
    Petri nets; computer science; processor scheduling; stochastic processes; virtual machines; virtual reality; computer science; lookahead computation; multiprocessor system; predictable scheduling; processor scheduling; stochastic petri nets; virtual computing systems; virtual machine; Application software; Computer networks; Computer science; Delay effects; Distributed computing; Multiprocessing systems; Processor scheduling; Scheduling algorithm; Stochastic processes; Web server;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-4507-3
  • Electronic_ISBN
    978-1-4244-4507-3
  • Type

    conf

  • DOI
    10.1109/CISE.2009.5365247
  • Filename
    5365247