Influence of different abstractions on the performance analysis of distributed hard real-time systems

Abstract

System level performance analysis plays a fundamental role in the design process of hard real-time embedded systems. Several different approaches have been presented so far to address the problem of accurate performance analysis of distributed embedded systems in early design stages. The existing formal analysis methods are based on essentially different concepts of abstraction. However, the influence of these different models on the accuracy of the system analysis is widely unknown, as a direct comparison of performance analysis methods has not been considered so far. We define a set of benchmarks aimed at the evaluation of performance analysis techniques for distributed systems. We apply different analysis methods to the benchmarks and compare the results obtained in terms of accuracy and analysis times, highlighting the specific effects of the various abstractions. We also point out several pitfalls for the analysis accuracy of single approaches and investigate the reasons for pessimistic performance predictions.

This is a preview of subscription content, access via your institution.

References

  1. 1.

    Alur R, Dill DL (1994) A theory of timed automata. Theor Comput Sci 126(2):183–235

    MATH  Article  MathSciNet  Google Scholar 

  2. 2.

    Behrmann G, David A, Larsen KG, Håkansson J, Pettersson P, Yi W, Hendriks M (2006) UPPAAL 4.0. In: Proc of the 3rd int conference on the quantitative evaluation of systems. IEEE Computer Society, Los Alamitos, pp 125–126

    Google Scholar 

  3. 3.

    Chakraborty S, Künzli S, Thiele L (2003) A general framework for analysing system properties in platform-based embedded system designs. In: Proc of 6th design, automation and test in Europe, pp 190–195

  4. 4.

    González Harbour M, Gutiérrez García JJ, Palencia Gutiérrez JC, Drake Moyano JM (2001) MAST: Modeling and analysis suite for real time applications. In: Proc of 13th Euromicro conference on real-time systems. IEEE Computer Society, Los Alamitos, pp 125–134

    Google Scholar 

  5. 5.

    Hendriks M, Verhoef M (2006) Timed automata based analysis of embedded system architectures. In: Workshop on parallel and distributed real-time systems

  6. 6.

    Henia R, Hamann A, Jersak M, Racu R, Richter K, Ernst R (2005) System level performance analysis—the SymTA/S approach. IEE Proc Comput Digit Tech 152(2):148–166

    Article  Google Scholar 

  7. 7.

    Le Boudec JY, Thiran P (2001) Network calculus: a theory of deterministic queuing systems for the Internet. Springer, New York

    Google Scholar 

  8. 8.

    Lehoczky J (1990) Fixed priority scheduling of periodic task sets with arbitrary deadlines. In: Proc of the real-time systems symposium, pp 201–209

  9. 9.

    Medina JL, González Harbour M, Drake JM (2001) MAST real-time view: a graphic UML tool for modeling object-oriented real-time systems. In: Proc of the 22nd real-time systems symposium. IEEE Computer Society, Los Alamitos, pp 245–256

    Google Scholar 

  10. 10.

    Norström C, Wall A, Yi W (1999) Timed automata as task models for event-driven systems. In: Proc of the 6th int conference on real-time computing systems and applications. IEEE Computer Society, Los Alamitos, p 182

    Google Scholar 

  11. 11.

    Palencia JC, González Harbour M (1999) Exploiting precedence relations in the schedulability analysis of distributed real-time systems. In: Proc of the 20th real-time systems symposium. IEEE Computer Society, Los Alamitos, pp 328–339

    Google Scholar 

  12. 12.

    Palencia Gutiérrez JC, González Harbour M (1998) Schedulability analysis for tasks with static and dynamic offsets. In: Proc of the 19th real-time systems symposium. IEEE Computer Society, Los Alamitos

    Google Scholar 

  13. 13.

    Perathoner S, Wandeler E, Thiele L (2006) Evaluation and comparison of performance analysis methods for distributed embedded systems. Technical report 276, Computer Engineering and Networks Laboratory, ETH Zurich, March 2006

  14. 14.

    Pop P, Eles P, Peng Z (2000) Performance estimation for embedded systems with data and control dependencies. In: Proc of the 8th int workshop on hardware/software codesign. ACM Press, New York, pp 62–66

    Google Scholar 

  15. 15.

    Pop T, Eles P, Peng Z (2002) Holistic scheduling and analysis of mixed time/event-triggered distributed embedded systems. In: Proc of the 10th int symposium on hardware/software codesign. ACM Press, New York, pp 187–192

    Google Scholar 

  16. 16.

    Richter K (2004) Compositional performance analysis. PhD thesis, Technical University of Braunschweig

  17. 17.

    Richter K, Jersak M, Ernst R (2003) A formal approach to MpSoC performance verification. IEEE Comput 36(4):60–67

    Google Scholar 

  18. 18.

    Schliecker S, Ernst R (2008) Compositional path latency computation with local busy times. Technical report TR-08-01, Institute of Computer and Communication Network Engineering, Technische Universität Braunschweig, Germany, January 2008

  19. 19.

    Thiele L, Chakraborty S, Gries M, Maxiaguine A, Greutert J (2001) Embedded software in network processors—models and algorithms. In: Proc of the 1st int workshop on embedded software. Springer, Berlin, pp 416–434

    Google Scholar 

  20. 20.

    Thiele L, Chakraborty S, Naedele M (2000) Real-time calculus for scheduling hard real-time systems. In: Proc int symposium on circuits and systems, vol 4, pp 101–104

  21. 21.

    Tindell K, Clark J (1994) Holistic schedulability analysis for distributed hard real-time systems. Microprocess Microprogram—Euromicro J 40:117–134 (Special Issue on Parallel Embedded Real-Time Systems)

    Article  Google Scholar 

  22. 22.

    Wandeler E, Thiele L (2005) Characterizing workload correlations in multi processor hard real-time systems. In: Proc of the 11th real time on embedded technology and applications symposium. IEEE Computer Society, Los Alamitos, pp 46–55

    Google Scholar 

  23. 23.

    Yen TY, Wolf W (1995) Performance estimation for real-time distributed embedded systems. In: Proc of the 1995 int conference on computer design. IEEE Computer Society, Los Alamitos, pp 64–71

    Google Scholar 

Download references

Author information

Affiliations

Authors

Corresponding author

Correspondence to Simon Perathoner.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Perathoner, S., Wandeler, E., Thiele, L. et al. Influence of different abstractions on the performance analysis of distributed hard real-time systems. Des Autom Embed Syst 13, 27–49 (2009). https://doi.org/10.1007/s10617-008-9015-1

Download citation

Keywords

  • Performance analysis
  • System abstraction
  • Benchmarking