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Complexity Challenges in Development of Cyber-Physical Systems

  • Martin TörngrenEmail author
  • Ulf Sellgren
Chapter
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10760)

Abstract

In embarking towards Cyber-Physical Systems (CPS) with unprecedented capabilities it becomes essential to improve our understanding of CPS complexity and how we can deal with it. We investigate facets of CPS complexity and the limitations of Collaborating Information Processing Systems (CIPS) in dealing with those facets. By CIPS we refer to teams of humans and computer-aided engineering systems that are used to develop CPS. Furthermore, we specifically analyze characteristic differences among software and physical parts within CPS. The analysis indicates that it will no longer be possible to rely only on architectures and skilled people, or process and model/tool centered approaches. The tight integration of heterogeneous physical, cyber, CPS components, aspects and systems, results in a situation with interfaces and interrelations everywhere, each requiring explicit consideration. The role of model-based and computer aided engineering will become even more essential, and design methodologies will need to deeply consider interwoven systems and software aspects, including the hidden costs of software.

Keywords

Cyber-Physical Systems Complex systems Complexity Complexity management Systems engineering Software engineering 

Notes

Acknowledgements

Feedback and insights from Erik Herzog (SAAB), Martin Nilsson (RISE) and Tor Ericson (ÅF) are greatly acknowledged. We also acknowledge valuable feedback from the anonymous reviewers. This work has been partially supported by the European Commission H2020 projects Platforms4CPS and CPSE-Labs.

References

  1. Adamsson, N.: Interdisciplinary integration in complex product development: managerial implications of embedding software in manufactured goods. Ph.D. thesis, Department of Machine Design, KTH Royal Institute of Technology, Stockholm, Sweden (2007)Google Scholar
  2. Andersson, H.: Henric Andersson, senior expert, SAAB. CPS summerschool lecture, Halmstad (2017). https://www.youtube.com/playlist?list=PLRM7eLJHoNde-iM3ET-2-bHsh-KSAWLs3. Accessed Sept 2017
  3. Axelsson, J.: On how to deal with uncertainty when architecting embedded software and systems. In: Crnkovic, I., Gruhn, V., Book, M. (eds.) ECSA 2011. LNCS, vol. 6903, pp. 199–202. Springer, Heidelberg (2011).  https://doi.org/10.1007/978-3-642-23798-0_20CrossRefGoogle Scholar
  4. Axelsson, J., et al.: Notes on agile and safety-critical development. In: XP2015 ASCS Workshop (2015)Google Scholar
  5. Blackenfelt, M.: Managing complexity by product modularization. Ph.D. thesis, Department of Machine Design, KTH Royal Institute of Technology, Stockholm, Sweden (2001)Google Scholar
  6. Blondel, V.D., Tsitsiklis, J.N.: A survey of computational complexity results in systems and control. Automatica 36(2000), 1249–1274 (2000)MathSciNetCrossRefGoogle Scholar
  7. Boyes, H.A.: Trustworthy cyber-physical systems—a review. In: 8th IET International System Safety Conference Incorporating the Cyber Security Conference (2013)Google Scholar
  8. Brooks, F.P.: No silver bullet: essence and accidents of software engineering. Computer 20(4), 10–19 (1987)CrossRefGoogle Scholar
  9. Broy, M.: Multifunctional software systems: structured modeling and specification of functional requirements. Sci. Comput. Program. 75(12), 1193–1214 (2010)CrossRefGoogle Scholar
  10. Broy, M., et al.: Engineering automotive software. Proc. IEEE 95(2), 356–373 (2007)CrossRefGoogle Scholar
  11. Börjesson, F.: Product platform design – architecting methods and tools. Ph.D. thesis, Department of Machine Design, KTH Royal Institute of Technology, Stockholm (2014)Google Scholar
  12. Checkland, P.: Systems Thinking, Systems Practice. Wiley, New York (2000)Google Scholar
  13. Cengarle, M.V., Bensalem, S., McDermid, J., Passerone, R., Sangiovanni-Vincentelli, A., Törngren, M.: CyPhERS: Characteristics, capabilities, potential applications of Cyber-Physical Systems: a preliminary analysis, Deliverable D2.1 of the CyPhERS FP7 project, November 2013. http://www.cyphers.eu/sites/default/files/D2.1.pdf. Accessed Sept 2017
  14. Derler, P., et al.: Modeling cyber-physical systems. Proc. IEEE Spec. Issue CPS 100(1), 13–28 (2012)Google Scholar
  15. El-khoury, J., et al.: A model-driven engineering approach to software tool interoperability based on linked data. Int. J. Adv. Softw. 9(3 & 4), 248–259 (2016)Google Scholar
  16. Engell, S., et al.: CPSoS: D3.2 Policy Proposal “European Research Agenda for Cyber-Physical Systems of Systems and their engineering needs”. Report D3.2 from the EU project CPSoS (Towards a European Roadmap on Research and Innovation in Engineering and Management of Cyber-Physical Systems of Systems) (2015)Google Scholar
  17. Ericson: Personnel communication with Tor Ericson, senior manager at ÅF (2017)Google Scholar
  18. Eppinger, S.D., Browning, T.R.: Design Structure Matrix Methods and Applications. MIT Press, London (2012)Google Scholar
  19. Eppinger, S., Salminen, V.: Patterns of Product Development Interactions. Int. Conf. on Engineering Design, ICED 01, Glasgow, August 2001Google Scholar
  20. ESD: ESD symposium committee overview: engineering systems research and practice. Engineering Systems Division MIT (2003). http://esd.mit.edu/ESD_Internal_Symposium_Docs/WPS/ESD-WP-2003-01.20ESD_InternalSymposium.pdf. Accessed Sept 2017
  21. Henzinger, T.A., Sifakis, J.: The embedded systems design challenge. In: Misra, J., Nipkow, T., Sekerinski, E. (eds.) FM 2006. LNCS, vol. 4085, pp. 1–15. Springer, Heidelberg (2006).  https://doi.org/10.1007/11813040_1CrossRefGoogle Scholar
  22. Horváth, I., et al.: Order beyond chaos: introducing the notion of generation to characterize the continuously evolving implementations of cyber-physical systems. In: Proceedings of the ASME 2017 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, Cleveland, Ohio, USA, August 2017Google Scholar
  23. INCOSE: Systems Engineering Handbook: A Guide for System Life Cycle Processes and Activities, 4th edn. International Council of Systems Engineering. Wiley (2015)Google Scholar
  24. Jacobson, I., Lawson, H.: Software and systems. In: Jacobson, I., Lawson, H. (eds.) Software Engineering in the Systems Context, Chap. 1. College publications (2015)Google Scholar
  25. J3016: Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles. SAE Surface Vehicle Recommended Practice, September 2016Google Scholar
  26. Kahneman, D.: Thinking, Fast and Slow. Penguin Books Ltd. (2012). ISBN 9780141033570Google Scholar
  27. Kopetz, H.: Real-Time Systems - Design Principles for Distributed Embedded Applications. Springer, Heidelberg (2011).  https://doi.org/10.1007/978-1-4419-8237-7CrossRefzbMATHGoogle Scholar
  28. Kaushik, S.: Structural complexity and its implications for design of cyber-physical systems. Ph.D. thesis. MIT Engineering Systems Division, September 2014Google Scholar
  29. Lawson, H.: Attaining a systems perspective. In: Jacobson, I., Lawson, H. (eds.) Software Engineering in the Systems Context. College publications (2015)Google Scholar
  30. Lee, E.A.: Computing needs time. Commun. ACM 52(5), 70–79 (2009)CrossRefGoogle Scholar
  31. Lee, E.A.: Fundamental limits of cyber-physical systems modeling. ACM Trans. Cyber-Phy. Syst. 1, 3:1–3:26 (2016). Article no. 3Google Scholar
  32. Maier, M.: Dimensions of complexity other than “complexity”. In: Symposium on Complex Systems Engineering. RAND Corporation, Santa Monica, CA, 11–12 January 2007Google Scholar
  33. Maier, M., Rechtin, E.: The Art of Systems Architecting. CRC Press, Boca Raton (2002)zbMATHGoogle Scholar
  34. Malvius, D.: Integrated information management in complex product development. Ph.D. thesis, Department of Machine Design, KTH Royal Institute of Technology, Sweden (2009)Google Scholar
  35. McConnell, S.: Software Project Survival Guide (Developer Best Practices). Microsoft Press, Redmond (1997)Google Scholar
  36. McDermid, J., Kelly, T.: Software in safety critical systems: achievement and prediction. Nucl. Future 02(03) (2006)Google Scholar
  37. Mohan, N., et al.: ATRIUM - architecting under uncertainty: for ISO 26262 compliance. In: IEEE SysCon (2017)Google Scholar
  38. National Academies: A 21st Century Cyber-Physical Systems Education. National Academies of Sciences, Engineering, and Medicine. National Academies Press (2016)Google Scholar
  39. NIST (2017). https://www.nist.gov/el/cyber-physical-systems. Accessed Sept 2017
  40. Oliver, D.W., et al.: Engineering Complex Systems with Models and Objects. McGraw-Hill, New York (1996)Google Scholar
  41. Platforms4CPS (2017). (see Foundations of CPS – Related Work). https://platforum.proj.kth.se/tiki-index.php?page=HomePageExternal. Accessed Sept 2017
  42. Qamar, A.: Model and dependency management in mechatronic design. Ph.D. thesis, KTH Royal Institute of Technology, Stockholm, Sweden (2013). ISBN 978-91-7501-664-1Google Scholar
  43. Qian, L., Gero, J.S.: Function-behavior structure paths and their role in analogy-based design. Artif. Intell. Eng. Des. Anal. Manuf. 10, 289–312 (1996)CrossRefGoogle Scholar
  44. Red, E., Jensen, G., Weerakoon, P., French, D., Benzley, S.: Architectural Limitations in Multi-User Computer-Engineering Applications. Center for e-Design Publications 7 (2013). http://lib.dr.iastate.edu/edesign_pubs/7. Accessed Sept 2017
  45. Sadigh, D., Kapoor, A.: Safe control under uncertainty with probabilistic signal temporal logic. In: Proceedings of Robotics: Science and Systems (RSS), June 2016.  https://doi.org/10.15607/RSS.2016.XII.017
  46. Sangiovanni-Vincentelli, A.: Defining platform-based design. EEDesign of EETimes (2002)Google Scholar
  47. Schätz, B., et al.: Research Agenda and Recommendations for Action, Deliverable of the CyPhERS FP7 Project, March 2015Google Scholar
  48. Sellgren, U.: Simulation driven design – motives, means, and opportunities. Ph.D. thesis, Department of Machine Design, KTH, Stockholm, Sweden (1999)Google Scholar
  49. Shannon, C.E., Weaver, W.: The Mathematical Theory of Communication. The University of Illinois Press, Urbana (1949)zbMATHGoogle Scholar
  50. Sheard, S.: Complexity, systems and software. In: Jacobson, I., Lawson, H. (eds.) Software Engineering in the Systems Context. College Publications (2015)Google Scholar
  51. Simon, H.: The Sciences of the Artificial, 3rd edn. MIT Press, Cambridge (1996)Google Scholar
  52. Simmons, W., et al.: Architecture generation for moon-mars exploration using an executable meta-language, vol. AIAA-2005-6726. American Institute of Aeronautics and Astronautics (2005)Google Scholar
  53. Sillitto, H.G.: On systems architects and systems architecting: some thoughts. In: Proceedings INCOSE, Singapore (2009)Google Scholar
  54. Song, H., et al.: CPS: Cyber-Physical Systems: Foundations, Principles and Applications. Elsevier, New York, September 2016. ISBN 9780128038017Google Scholar
  55. Steward, D.V.: The design structure system: a method for managing the design of complex systems. IEEE Trans. Eng. Manag. EM-28 (1981).  https://doi.org/10.1109/tem.1981.6448589. Accessed Sept 2017
  56. Suh, N.P.: The Principles of Design. Oxford University Press, New York (1990)Google Scholar
  57. Suh, N.P.: A theory of complexity, periodicity and the design axioms. Res. Eng. Des. 11(2), 116–132 (1999)CrossRefGoogle Scholar
  58. Thomas Telford Journals M-W (2017). Merriam-Webster: https://www.merriam-webster.com/dictionary/cyber. Accessed Sept 2017
  59. Törngren, M., et al.: Model based development of automotive embedded systems. In: Navet, N., Simonot-Lion, F. (eds.) Automotive Embedded Systems Handbook. Taylor and Francis CRC Press Series. Industrial Information Tech (2008)Google Scholar
  60. Törngren, M., et al.: Integrating viewpoints in the development of mechatronic products. J. Mechatron. 24(7), 745–762 (2014)CrossRefGoogle Scholar
  61. Törngren, M., et al.: Education and training challenges in the era of Cyber-Physical Systems: beyond traditional engineering. In: Workshop on Embedded and Cyber-Physical Systems Education (WESE) at ESWEEK 2015, Amsterdam (2015)Google Scholar
  62. Törngren, M., et al.: Strategies and considerations in shaping cyber-physical systems education. ACM SIGBED Rev. – Spec. Issue Embed. Cyber-Phys. Syst. Educ. 14(1), 53–60 (2016)Google Scholar
  63. VDI: Design methodology for mechatronic systems - VDI 2206. VDI Guidelines, Beuth Berlin (2004)Google Scholar
  64. Wagner, M., Koopman, P.: A philosophy for developing trust in self-driving cars. In: Meyer, G., Beiker, S. (eds.) Road Vehicle Automation 2. LNM, pp. 163–171. Springer, Cham (2015).  https://doi.org/10.1007/978-3-319-19078-5_14CrossRefGoogle Scholar
  65. Westman, J.: Specifying safety-critical heterogeneous systems using contracts theory. Ph.D. thesis, KTH Royal Institute of Technology (2016)Google Scholar
  66. Whitney, D.E.: Why mechanical design cannot be like VLSI design. Res. Eng. Des. 8, 125–128 (1996)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.KTH Royal Institute of TechnologyStockholmSweden

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