• DocumentCode
    526977
  • Title

    The preemptive EDF optimization based on DNA-Genetic Algorithm

  • Author

    Zhao, Yuan-qing ; Jin, Xian-hua ; Liu, Yong

  • Author_Institution
    Sch. of Comput. & Inf. Eng., Anyang Normal Univ., Anyang, China
  • Volume
    2
  • fYear
    2010
  • fDate
    17-18 July 2010
  • Firstpage
    121
  • Lastpage
    124
  • Abstract
    Earliest Deadline First (EDF) is a favorable algorithm in the field of dynamic scheduling which plans the task scheduling during system running. The CPU utilization of EDF algorithm may achieve to one hundred percent. Although EDF has many excellent performances and is used broadly in actual embedded real-time systems, it has many shortages. In order to reduce the release time of EDF scheduling algorithm and to decrease scheduling spending, the Deoxyribonucleic acid Genetic Algorithm (DNA-GA) is used to optimize the preemptive EDF scheduling algorithm in off-line model. Simulation experiments are carried out to compare the performances. Compared with the scheduling spending before optimized, the scheduling spending after optimized was reduced dramatically and the real-time performance was improved.
  • Keywords
    genetic algorithms; scheduling; CPU utilization; deoxyribonucleic acid genetic algorithm; earliest deadline first; preemptive EDF optimization; task scheduling; Optimization; DNA-GA; EDF; real-time scheduling; real-time system; schedulability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Environmental Science and Information Application Technology (ESIAT), 2010 International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-7387-8
  • Type

    conf

  • DOI
    10.1109/ESIAT.2010.5567289
  • Filename
    5567289