A Fuzzy Scheduling Algorithm Based on Highest Response Ratio Next Algorithm

  • Ali Moallemi
  • Mohsen Asgharilarimi
Conference paper

Abstract

The field of fuzzy systems and control has been making rapid progress in recent years. Fuzzy logic in a wider sense is a nonlinear mapping from the inputs to the output of the system. It has a variety of applications. In this paper, we have applied it for process scheduling. We propose a fuzzy logic process scheduler in CPU, which uses the idea of HRN (Highest Response Ratio Next) scheduling algorithm as its method of inference and decides based on this manner. Because of the approximate nature of the Service Time of processes, a fuzzy logic algorithm would help us set priorities to processes in a more appropriate and fair manner. At the end, we compare our work with the existing conventional process scheduling algorithms and give the comparison graphs for our evaluation. Our algorithm has precise priority values and does not need any other scheduling algorithm concurrently. It also has a better evaluation output compared with other existing algorithms.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [1]
    Li-Xin. Wang. A course in fuzzy systems and control. Prentice-Hall, Inc. 1996.Google Scholar
  2. [2]
    Silberschatz, Galvin and Gagne. Operating System Concepts – 7th Edition, Feb, 2005.Google Scholar
  3. [3]
    P. Goyal, X. Guo, and H.M. Vin. A Hierarchical CPU Scheduler for Multimedia Operating Systems. In Proceedings of Operating System Design and Implementation (OSDI’96), Seattle, pages 107–122, October 1996.Google Scholar
  4. [4]
    L. Bush. Fuzzy Logic Controller for the Inverted Pendulum Problem. A workshop on fuzzy logic controller. Computer Science Department, Rensselaer Polytechnic Institute, New York, November 2001.Google Scholar
  5. [5]
    Fuzzy Logic Toolbox User’s Guide. © COPYRIGHT 1995 — 2006 The MathWorks, Inc.Google Scholar
  6. [6]
    M B. Jones and J. Regehr. CPU Reservations and Time Constraints: Implementation Experience on Windows NT. In Proceedings of the Third Windows NT Symposium, Seattle, WA, July 1999.Google Scholar
  7. [7]
    A. Mok and M. Dertouzos. Multiprocessor Scheduling in a Hard Real-time Environment. In Proceedings of the Seventh Texas Conf. on Computing Systems, November 1978.Google Scholar
  8. [8]
    J. Nieh and M. S. Lam. Multimedia on Multiprocessors: Where’s the OS When You Really Need It? In Proceedings of the Eighth International Workshop on Network and Operating System Support for Digital Audio and Video, Cambridge,U.K., July 1998.Google Scholar
  9. [9]
    L. A. Zadeh, ∖Fuzzy Sets, Information and Control, vol. 8, pp.338-353, 1965.MATHCrossRefMathSciNetGoogle Scholar
  10. [10]
    J. Yen, ∖Fuzzy Logic|A Modern Perspective,” IEEE Trans- actions on Knowledge and Data Engineering, vol. 11, no. 1, pp. 153-165, 1999.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2008

Authors and Affiliations

  • Ali Moallemi
    • 1
  • Mohsen Asgharilarimi
    • 1
  1. 1.Department of Mathematics and Statistics Faculty of ScienceGorgan University of Agricultural Sciences and Natural ResourcesGorganIran

Personalised recommendations