Fuzzy rule-based approach to real-time scheduling

Jonathan Lee, Amos Tiao, John Yen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

30 Scopus citations

Abstract

In real-time systems, tasks have to be performed not only correctly, but in a timely fashion. Task scheduling is essential for designing a real-time system, because the scheduling algorithm ensures if tasks meet their deadlines. However, the inherit nature of uncertainty in dynamic real-time systems increases the problems inherent in scheduling. To alleviate these problems, we proposed a fuzzy scheduling approach in which the real-time scheduling problem is treated as a multi-criteria optimization problem, and a set of fuzzy rules is utilized to derive a feasible schedule. A simulation is also conducted to evaluate the performance of the proposed approach. The result of the simulation shows that the proposed fuzzy scheduler performs very closed to the optimal minimum laxity first (MLF) in terms of task loss, and performs significantly better than MLF in choosing important tasks to execute.

Original languageEnglish (US)
Title of host publicationIEEE International Conference on Fuzzy Systems
PublisherIEEE
Pages1394-1399
Number of pages6
Volume2
StatePublished - 1994
EventProceedings of the 3rd IEEE Conference on Fuzzy Systems. Part 3 (of 3) - Orlando, FL, USA
Duration: Jun 26 1994Jun 29 1994

Other

OtherProceedings of the 3rd IEEE Conference on Fuzzy Systems. Part 3 (of 3)
CityOrlando, FL, USA
Period6/26/946/29/94

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Software
  • Artificial Intelligence
  • Applied Mathematics

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