Advertisement

Architectural Support for Model-Driven Performance Prediction of Distributed Real-Time Embedded Systems of Systems

  • Vanea Chiprianov
  • Katrina Falkner
  • Claudia Szabo
  • Gavin Puddy
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8627)

Abstract

Systems of systems (SoS) are large-scale systems composed of complex systems with difficult to predict emergent properties. One of the most significant challenges in the engineering of such systems is how to predict their non-functional properties such as performance, and more specifically, how to model non-functional properties when the overall system functionality is not available. In this paper, we define an approach to SoS performance prediction based on the modelling of system interactions and their impacts. We adopt an Event Driven Architecture to support this modelling, as it allows for more realistic and flexible performance simulation, which enables more accurate performance prediction. We introduce a generic architecture and present its instantiation in a software architecture for the performance prediction of defence SoS. Our architecture allows for loose coupling, interoperability, and adaptability and facilitates sustainable evolution of the performance model of the SoS.

Keywords

Performance Prediction Software Architecture Event Channel Loose Coupling Architectural Support 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Jamshidi, M.: System of systems engineering - new challenges for the 21st century. IEEE Aerospace and Electronic Systems Magazine 23(5), 4–19 (2008)CrossRefGoogle Scholar
  2. 2.
    Dagli, C.H., Kilicay-Ergin, N.: System of Systems Architecting, pp. 77–100. John Wiley & Sons, Inc. (2008)Google Scholar
  3. 3.
    Manthorpe, W.H.: The Emerging Joint System of Systems: A Systems Eng. Challenge and Opportunity for APL. J. Hopkins APL Tech. Digest 17, 305–310 (1996)Google Scholar
  4. 4.
    Balsamo, S., Marco, A.D., Inverardi, P., Simeoni, M.: Model-based performance prediction in soft. dev.: a survey. IEEE Trans. on Soft. Eng. 30, 295–310 (2004)CrossRefGoogle Scholar
  5. 5.
    Beydeda, S., Book, M., Gruhn, V. (eds.): Model Driven Software Development. Spinger (2010)Google Scholar
  6. 6.
    Hill, J., Schmidt, D., Slaby, J.: System Execution Modeling Tools for Evaluating the Quality of Service of Enterprise Distributed Real-time and Embedded Systems. In: Designing Software-Intensive Systems: Methods and Principles, pp. 335–371 (2008)Google Scholar
  7. 7.
    Paunov, S., Hill, J., Schmidt, D., Baker, S., Slaby, J.: Domain-Specific Modeling Languages for Configuring and Evaluating Enterprise DRE System Quality of Service. In: 13th IEEE Intl Symp and Wksh on Eng. of Comp. Based Sys. (2006)Google Scholar
  8. 8.
    Hill, J., Schmidt, D., Edmondson, J., Gokhale, A.: Tools for continuously evaluating distributed system qualities. IEEE Software 27(4), 65–71 (2010)CrossRefGoogle Scholar
  9. 9.
    Michelson, B.M.: Event-driven architecture overview. Technical report, Patricia Seybold Group (2006)Google Scholar
  10. 10.
    Schmidt, D.C., Stal, M., Rohnert, H., Bushmann, F.: Pattern-oriented Software Architecture: Patterns for Concurrent and Networked Objects. Wiley (2000)Google Scholar
  11. 11.
    Falkner, K., Chiprianov, V., Falkner, N., Szabo, C., Puddy, G.: Modeling scenarios for the performance prediction of distributed real-time embedded systems. In: Military Communications and Inf. Systems Conf., Canberra, Australia, pp. 1–6 (2013)Google Scholar
  12. 12.
    Falkner, K., Chiprianov, V., Falkner, N., Szabo, C., Puddy, G.: A model driven engineering method for DRE defence systems performance analysis and prediction. In: Bagnato, A., Indrusiak, L.S., Quadri, I.R., Rossi, M.G. (eds.) Industry and Research Perspectives on Embedded System Design. IGI-Global (accepted, 2014)Google Scholar
  13. 13.
    Falkner, K., Chiprianov, V., Falkner, N., Szabo, C., Hill, J., Puddy, G., Fraser, D., Johnston, A., Rieckmann, M., Wallis, A.: Model-driven performance prediction of distributed real-time embedded defence systems. In: The 18th Intl Conf. on Engineering of Complex Computer Systems, Singapore, pp. 155–158 (2013)Google Scholar
  14. 14.
    Klein, J., van Vliet, H.: A Systematic Review of System-of-systems Architecture Research. In: The 9th Intl ACM Sigsoft Conf. on Quality of Software Architectures, QoSA 2013, pp. 13–22. ACM, New York (2013)Google Scholar
  15. 15.
    Ge, B., Hipel, K.W., Yang, K., Chen, Y.: A data-centric capability-focused approach for system-of-systems architecture modeling and analysis. Systems Engineering 16(3), 363–377 (2013)CrossRefGoogle Scholar
  16. 16.
    Volkert, R., Stracener, J.T., Yu, J.: A framework for performance prediction during development of systems of systems. Intl J. of System of Syst. Eng. 3, 76–95 (2012)CrossRefGoogle Scholar
  17. 17.
    Smith, C.: Introduction to soft. performance engineering: origins and outstanding problems. In: 7th Intl. Conf. on Formal Meth. for Perf. Evaluation, pp. 395–428 (2007)Google Scholar
  18. 18.
    Koziolek, H.: Performance evaluation of component-based software systems: A survey. Performance Evaluation 67(8), 634–658 (2010)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Vanea Chiprianov
    • 1
  • Katrina Falkner
    • 1
  • Claudia Szabo
    • 1
  • Gavin Puddy
    • 1
  1. 1.School of Computer ScienceUniversity of AdelaideAustralia

Personalised recommendations