Advertisement

A case study in quantitative evaluation of real-time software architectures

  • José L. Fernández
  • Bárbara álvarez
  • Francisco García
  • ángel Pérez
  • Juan A. de la Puente
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1411)

Abstract

Generic architectures for specific domains can provide significant gains in productivity and quality for real-time systems development. In order to choose among different architectural features, a variety of qualitative criteria have been proposed in the literature. However, real-time systems require a more exact characterization based on quantitative evaluation of some architectural features related to timing properties, such as scalability. In this paper we explore a possible way of using Rate Monotonic Analysis to get a measure of scalability between alternative architectures. The technique is illustrated with a case study in a well-known real-time domain, data acquisition systems. The results show clear differences in scalability for different architectures, giving a clear indication of which one is better from this point of view. We believe that the approach can be used on other properties and domain architectures, thus opening new possibilities for quantitative evaluation of software architectures.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Reference Manual for the Ada Programming Language (1983). ANSI/MIL-STD-1815A-1983;ISO/8652:1987.Google Scholar
  2. 2.
    A. Alonso, B. álvarez, J.A. Pastor, J.A. de la Puente, A. Iborra (1997). “Software Architecture for a Robot Teleoperation System.” Proc. IFAC Symposium on Algorithms and Architectures for Real-Time Control. Elsevier Science, 1997.Google Scholar
  3. 3.
    N.C. Audsley, A. Burns, R.I Davis, K. Tindell, and A.J. Wellings (1995). “Fixed Priority Pre-emptive Scheduling: An Historical Perspective.” Real-Time Systems, vol. 8, no. 2/3, pp. 173–198.CrossRefGoogle Scholar
  4. 4.
    C.M. Bailey, A. Burns, A.J. Wellings, and C.H. Forsyth (1995). “A Performance Analysis of a Hard Real-Time System.” Control Engineering Practice. Vol. 3 No 4: 447–464.CrossRefGoogle Scholar
  5. 5.
    R.J.A. Buhr, (1990). Practical Visual Techniques in System Design. Prentice Hall.Google Scholar
  6. 6.
    R.M. Clapp and T. Mudge (1990). “The Time Problem.” ACM Ada Letters, Vol. X, No. 3: 20–28.CrossRefGoogle Scholar
  7. 7.
    J.L Fernández (1993). “A Taxonomy of Coordination Mechanisms Used in Real-Time Software Based on Domain Analysis.” Technical Report CMU/SEI-93-TR-34, Software Engineering Institute, Pittsburgh, PA.Google Scholar
  8. 8.
    J.L. Fernández, A. Pérez, B. álvarez and F. García (1995). “Performance Engineering of Real-Time Laboratory Automation Software Architectures.” Technical Report DIT/UPM 1995/01.Google Scholar
  9. 9.
    J.L Fernández (1997). “A Taxonomy of Coordination Mechanisms Used by Real-Time Processes.” ACM Ada Letters, vol. XVII, no. 2: 29–54.CrossRefGoogle Scholar
  10. 10.
    D. Garlan and M. Shaw (1996). Software Architecture: Perspectives on an Emerging Discipline. Prentice-Hall.Google Scholar
  11. 11.
    M.González-Harbour, M.H. Klein and J.P. Lehoczky (1991). “Fixed Priority Scheduling of Periodic Tasks with Varying Execution Priority.” Proceedings of the IEEE Real-Time Systems Symposium. Los Alamitos, C.A. pp.116–128.Google Scholar
  12. 12.
    R. House (1995). “Choosing the Right Software for Data Acquisition.” IEEE Spectrum. May 1995: 24–39.CrossRefGoogle Scholar
  13. 13.
    M.H. Klein, T. Ralya, B. Pollak, R. Obenza and M. Gonzalez-Harbour. (1993). A Practitioner's Handbook for Real-Time Analysis: Guide to Rate Monotonic Analysis for Real-Time Systems. Kluwer Academic Publishers.Google Scholar
  14. 14.
    C.L. Liu and J.W. Layland (1973). “Scheduling Algorithms for Multi-Programming in a Hard Real-Time Environment.“ ACM Journal. 20, 1: 40–61.MathSciNetGoogle Scholar
  15. 15.
    K. Nielsen and K. Shumate (1988). Designing Large Real-Time Systems with Ada. McGraw-Hill.Google Scholar
  16. 16.
    R. Obenza (1993). “Rate Monotonic Analysis for Real-Time Systems.” IEEE Computer. Vol. 26, No 3: 73–74.Google Scholar
  17. 17.
    D. Roy (1990). “PIWG Measurement Methodology.” ACM Ada Letters. Vol X No 3: 72–90.CrossRefGoogle Scholar
  18. 18.
    B. Sanden (1989). “Entity-Life Modeling and Structured Analysis in Real-Time Software Design. A comparison.” Communications ACM. Vol. 32 No. 12: 1458–1466.CrossRefGoogle Scholar
  19. 19.
    L. Sha and J.B. Goodenough (1990). “Real Time Scheduling Theory and Ada.” IEEE Computer. Vol. 23, No 4: 53–62.Google Scholar
  20. 20.
    B. Witt, T. Baker, and E. Merrit (1994). Software Architecture and Design. Principles, Models and Methods. Van Nostrand Reinhold.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • José L. Fernández
    • 1
  • Bárbara álvarez
    • 1
  • Francisco García
    • 1
  • ángel Pérez
    • 1
  • Juan A. de la Puente
    • 1
  1. 1.Departamento de Ingeniería de Sistemas TelemáticosUniversidad Politécnica de Madrid ETSI TelecomunicaciónMadrid

Personalised recommendations