Scheduling of tasks in multiprocessor system using hybrid genetic algorithms

Betzy Varghes, Alamgir Hossain, Keshav Dahal

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

This paper presents an investigation into the optimal scheduling of real-time tasks of a multiprocessor system using hybrid genetic algorithms (GAs). A comparative study of heuristic approaches such as ‘Earliest Deadline First (EDF)’ and ‘Shortest Computation Time First (SCTF)’ and genetic algorithm is explored and demonstrated. The results of the simulation study using MATLAB is presented and discussed. Finally, conclusions are drawn from the results obtained that genetic algorithm can be used for scheduling of real-time tasks to meet deadlines, in turn to obtain high processor utilization.
Original languageEnglish
Title of host publicationApplications of Soft Computing
EditorsE. Avineri, M. Köppen, K. Dahal, Y. Sunitiyoso, R. Roy
PublisherSpringer Berlin Heidelberg
Pages65-74
Number of pages10
ISBN (Electronic)9783540880790
ISBN (Print)9783540880783
DOIs
Publication statusPublished - 2009
Externally publishedYes

Publication series

NameAdvances in Soft Computing
PublisherSpringer
Volume52

Keywords

  • optimal scheduling
  • hard real-time tasks
  • multiprocessor system
  • heuristics
  • genetic algorithm

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