Software & Systems Modeling

, Volume 18, Issue 1, pp 739–767 | Cite as

Synthesis and exploration of multi-level, multi-perspective architectures of automotive embedded systems

  • Jordan A. RossEmail author
  • Alexandr Murashkin
  • Jia Hui Liang
  • Michał Antkiewicz
  • Krzysztof Czarnecki
Regular Paper


In industry, evaluating candidate architectures for automotive embedded systems is routinely done during the design process. Today’s engineers, however, are limited in the number of candidates that they are able to evaluate in order to find the optimal architectures. This limitation results from the difficulty in defining the candidates as it is a mostly manual process. In this work, we propose a way to synthesize multi-level, multi-perspective candidate architectures and to explore them across the different layers and perspectives. Using a reference model similar to the EAST-ADL domain model but with a focus on early design, we explore the candidate architectures for two case studies: an automotive power window system and the central door locking system. Further, we provide a comprehensive set of question templates, based on the different layers and perspectives, that engineers can ask to synthesize only the candidates relevant to their task at hand. Finally, using the modeling language Clafer, which is supported by automated backend reasoners, we show that it is possible to synthesize and explore optimal candidate architectures for two highly configurable automotive sub-systems.


Architecture synthesis Multi-level architectures Multi-perspective architectures E/E architecture Architecture optimization Candidate architectures Early design 


  1. 1.
    Archeopterix: Last accessed 21 Feb 2017
  2. 2.
    Autofocus 3: Last accessed 21 Feb 2017
  3. 3.
    Clafer: Last accessed 21 Feb 2017
  4. 4.
    EAST-ADL domain model specification, version V2.1.12.: Last accessed 21 Feb 2017
  5. 5.
    OSATE, version 2.: Last accessed 21 Feb 2017
  6. 6.
    Aleti, A., Bjornander, S., Grunske, L., Meedeniya, I.: Archeopterix: An extendable tool for architecture optimization of aadl models. In: ICSE Workshop on Model-Based Methodologies for Pervasive and Embedded Software, 2009, MOMPES ’09. pp. 61–71 (2009)Google Scholar
  7. 7.
    Aleti, A., Buhnova, B., Grunske, L., Koziolek, A., Meedeniya, I.: Software architecture optimization methods: a systematic literature review. IEEE Trans. Softw. Eng. 39(5), 658–683 (2013)CrossRefGoogle Scholar
  8. 8.
    Antkiewicz, M., Bąk, K., Murashkin, A., Olaechea, R., Liang, J., Czarnecki, K.: Clafer tools for product line engineering. In: Software Product Line Conference (2013)Google Scholar
  9. 9.
    Bąk, K., Diskin, Z., Antkiewicz, M., Czarnecki, K., Wąsowski, A.: Clafer: unifying class and feature modeling. Softw. Syst. Model. 15(3), 811–845 (2016)CrossRefGoogle Scholar
  10. 10.
    Bosch Semiconductors: CAN literature. Last accessed 21 Feb 2017
  11. 11.
    Brandt, L., Krämer, N., Metzger, J., Lindemann, U., et al.: Optimization approach for function-partitioning in an automotive electric electronic system architecture. In: DS 70: Proceedings of DESIGN 2012 (2012)Google Scholar
  12. 12.
    Broy, M.: Challenges in automotive software engineering. In: 28th International Conference on Software Engineering, pp. 33–42 (2006)Google Scholar
  13. 13.
    Coit, D.W., Smith, A.E.: Solving the redundancy allocation problem using a combined neural network/genetic algorithm approach. Comput. Oper. Res. 23(6), 515–526 (1996)CrossRefzbMATHGoogle Scholar
  14. 14.
    Coit, D.W., Smith, A.E.: Redundancy allocation to maximize a lower percentile of the system time-to-failure distribution. IEEE Trans. Reliabil. 47(1), 79–87 (1998)CrossRefGoogle Scholar
  15. 15.
    Cuenot, P., Chen, D., Gerard, S., Lonn, H., Reiser, M.O., Servat, D., Sjostedt, C.J., Kolagari, R., Torngren, M., Weber, M.: Managing complexity of automotive electronics using the EAST-ADL. In: 12th IEEE International Conference on Engineering Complex Computer Systems, 2007, pp. 353–358 (2007)Google Scholar
  16. 16.
    Dave, B.P., Jha, N.K.: Cohra: hardware-software cosynthesis of hierarchical heterogeneous distributed embedded systems. IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst. 17(10), 900–919 (1998)CrossRefGoogle Scholar
  17. 17.
    Davis, R.I., Burns, A., Bril, R.J., Lukkien, J.J.: Controller area network (can) schedulability analysis: refuted, revisited and revised. Real-Time Syst. 35(3), 239–272 (2007)CrossRefGoogle Scholar
  18. 18.
    Feiler, P., Hansson, J.: Flow latency analysis with the architecture analysis and design language (AADL). Tech. Rep. CMU/SEI-2007-TN-010, Software Engineering Institute, Carnegie Mellon University, Pittsburgh, PA (2007).
  19. 19.
    Florentz, B., Huhn, M.: Embedded systems architecture: evaluation and analysis. In: Proceedings of the 2nd International Conference on Quality of Software Architectures, QoSA’06, pp. 145–162 (2006)Google Scholar
  20. 20.
    Glaß, M., Lukasiewycz, M., Wanka, R., Haubelt, C., Teich, J.: Multi-objective routing and topology optimization in networked embedded systems. In: Embedded Computer Systems: Architectures, Modeling, and Simulation 2008, 74–81 (2008)Google Scholar
  21. 21.
    Graf, S., Glaß, M., Teich, J., Lauer, C.: Multi-variant-based design space exploration for automotive embedded systems. In: Proceedings of the Conference on Design, Automation and Test in Europe, DAT ’14, pp. 7:1–7:6. European Design and Automation Association (2014)Google Scholar
  22. 22.
    Han, K., Kwon, Y., Kim, W., Cho, J.: Distributed hierarchical service network for automotive embedded system. In: Information Networking (ICOIN), pp. 188–192 (2012)Google Scholar
  23. 23.
    ISO: Road vehicles–local interconnect network (LIN)—part 6: Protocol conformance test specification (2015). ISO/DIS 17987-6.2Google Scholar
  24. 24.
    Jackson, D., Estler, H., Rayside, D., et al.: The guided improvement algorithm for exact, general-purpose, many-objective combinatorial optimization (2009)Google Scholar
  25. 25.
    Kang, E., Jackson, E., Schulte, W.: An approach for effective design space exploration. In: Foundations of Computer Software. Modeling, Development, and Verification of Adaptive Systems, pp. 33–54. Springer (2010)Google Scholar
  26. 26.
    Kang, K., Cohen, S., Hess, J., Novak, W., Peterson, A.: Feature-oriented domain analysis (foda) feasibility study. Tech. Rep. CMU/SEI-90-TR-021, Software Engineering Institute, Carnegie Mellon University, Pittsburgh, PA (1990).
  27. 27.
    Kugele, S., Pucea, G.: Model-based optimization of automotive E/E-architectures. In: Proceedings of the 6th International Workshop on Constraints in Software Testing, Verification, and Analysis, CSTVA 2014, pp. 18–29 (2014)Google Scholar
  28. 28.
    Li, R., Etemaadi, R., Emmerich, M.T.M., Chaudron, M.R.V.: An evolutionary multiobjective optimization approach to component-based software architecture design. In: Evolutionary Computation (CEC), pp. 432–439 (2011)Google Scholar
  29. 29.
    Lin, C.W., Rao, L., Giusto, P., D’Ambrosio, J., Sangiovanni-Vincentelli, A.L.: Efficient wire routing and wire sizing for weight minimization of automotive systems. IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst. 34(11), 1730–1741 (2015)CrossRefGoogle Scholar
  30. 30.
    Meedeniya, I.: Architecture optimisation of embedded systems under uncertainty in probabilistic reliability evaluation model parameters. Ph.D. thesis, Swinburne University of Technology, Melbourne, Australia (2012)Google Scholar
  31. 31.
    Meedeniya, I., Buhnova, B., Aleti, A., Grunske, L.: Architecture-driven reliability and energy optimization for complex embedded systems. In: Proceedings of the 6th International Conference on Quality of Software Architectures: Research into Practice—Reality and Gaps, QoSA’10, pp. 52–67 (2010)Google Scholar
  32. 32.
    Meedeniya, I., Buhnova, B., Aleti, A., Grunske, L.: Reliability-driven deployment optimization for embedded systems. J. Syst. Softw. 84(5), 835–846 (2011)CrossRefGoogle Scholar
  33. 33.
    Meedeniya, I., Moser, I., Aleti, A., Grunske, L.: Architecture-based reliability evaluation under uncertainty. In: Proceedings of the Joint ACM SIGSOFT Conference—QoSA and Symposium—ISARCS on Quality of Software Architectures, QoSA-ISARCS ’11, pp. 85–94 (2011)Google Scholar
  34. 34.
    Montgomery, J., Moser, I.: Parallel constraint handling in a multiobjective evolutionary algorithm for the automotive deployment problem. In: 6th IEEE International Conference on e-Science Workshops, 2010, pp. 104–109 (2010)Google Scholar
  35. 35.
    Murashkin, A.: Automotive electronic/electric architecture modeling, design exploration and optimization using Clafer. Master’s thesis, University of Waterloo (2014).
  36. 36.
    Murashkin, A., Antkiewicz, M., Rayside, D., Czarnecki, K.: Visualization and exploration of optimal variants in product line engineering. In: Software Product Line Conference (2013)Google Scholar
  37. 37.
    Nicholson, M., Burns, A., Dd, Y.: Emergence of an architectural topology for safety-critical real-time systems (1997)Google Scholar
  38. 38.
    Prud’homme, C., Fages, J.G., Lorca, X.: Choco3 Documentation. TASC, INRIA Rennes, LINA CNRS UMR 6241, COSLING S.A.S. (2014). Last accessed 21 Feb 2017
  39. 39.
    Ross, J., Antkiewicz, M., Czarnecki, K.: Case studies on E/E architectures for power window and central door locks systems (2016).
  40. 40.
    Schäuffele, J.: E/e architectural design and optimization using preevision. Tech. rep, SAE Technical Paper (2016)Google Scholar
  41. 41.
    Voss, S., Eder, J., Schaetz, B. (eds.).: Scheduling Synthesis for Multi-Period SW Components. SAE Technical Paper 2016-01-0012 (2016). doi: 10.4271/2016-01-0012
  42. 42.
    Voss, S., Schatz, B.: Deployment and scheduling synthesis for mixed-critical shared-memory applications. In: 20th IEEE International Conference and Workshops on the Engineering of Computer Based Systems (ECBS), 2013, pp. 100–109 (2013)Google Scholar
  43. 43.
    Zeller, M., Prehofer, C.: Modeling and efficient solving of extra-functional properties for adaptation in networked embedded real-time systems. J. Syst. Archit. 59(10), 1067–1082 (2013)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  • Jordan A. Ross
    • 1
    Email author
  • Alexandr Murashkin
    • 1
  • Jia Hui Liang
    • 1
  • Michał Antkiewicz
    • 1
  • Krzysztof Czarnecki
    • 1
  1. 1.University of WaterlooWaterlooCanada

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