• DocumentCode
    2373173
  • Title

    On-line real-time task scheduling on partitionable multiprocessors

  • Author

    Mohapatra, Prasant ; Ahn, ByungJun ; Shi, Jian-Feng

  • Author_Institution
    Dept. of Electr. Eng. & Comput. Eng., Iowa State Univ., Ames, IA, USA
  • fYear
    1996
  • fDate
    23-26 Oct 1996
  • Firstpage
    350
  • Lastpage
    357
  • Abstract
    Multiprocesssor systems have emerged as an important computing means for real-time applications and have received increasing attention than before. However until now, little research has been done on the problem of on-line scheduling of parallel tasks with deadlines in partitionable multiprocessor systems. In this paper, we propose a new on-line scheduling algorithm, called Deferred Earliest Deadline First (DEDF) for such systems. The main idea of the DEDF algorithm is to defer the scheduling as late as possible, so that a set of jobs is scheduled at a time instead of one at a time. For processor allocation using DEDF, we have introduced a new concept-Available Time Window (ATW). By using ATW the system utilization can be improved and thereby enabling the system to meet the deadline of more number of tasks. Simulation results for a hypercube indicate that the DEDF algorithm performs significantly better than the earlier proposed Buddy/RT and Stacking algorithms for a wide range of work loads
  • Keywords
    digital simulation; multiprocessing systems; performance evaluation; processor scheduling; real-time systems; DEDF algorithm; available time window; deferred earliest deadline first; hypercube; online real-time task scheduling; online scheduling algorithm; partitionable multiprocessors; processor allocation; real-time applications; simulation results; stacking algorithms; Application software; Hypercubes; Multiprocessing systems; Optimal scheduling; Processor scheduling; Real time systems; Scalability; Scheduling algorithm; Stacking; Time factors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel and Distributed Processing, 1996., Eighth IEEE Symposium on
  • Conference_Location
    New Orleans, LA
  • Print_ISBN
    0-8186-7683-3
  • Type

    conf

  • DOI
    10.1109/SPDP.1996.570354
  • Filename
    570354