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Dealing with Uncertainty in Software Architecture on the Internet-of-Things with Digital Twins

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11619))

Abstract

When architecting Software-intensive Systems-of-Systems (SoS) on the Internet-of-Things (IoT), architects face two sorts of uncertainties. First, they have only limited knowledge about the operational environment where the SoS will actually be deployed. Second, the constituent systems which will compose the SoS might not be known a priori (at design-time) or their availability (at run-time) is affected by dynamic factors, due to the openness of the IoT. The consequent research question is thereby how to deal with uncertainty in the design of an SoS architecture on the IoT. To tackle this challenging issue, this paper addresses the notion of uncertainty due to partial information in SoS and proposes an enhanced SoS Architecture Description language (SosADL) for expressing SoS architectures on the IoT under uncertainty. The core SosADL is extended with concurrent constraints and the concept of digital twins coupling the physical and virtual worlds. This novel approach is supported by an integrated toolset, the SosADL Studio. Validation results demonstrate its effectiveness in an SoS architecture for platooning of self-driving vehicles.

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References

  1. Ayyub, B., Klir, G.: Uncertainty Modeling and Analysis in Engineering and the Sciences. Chapman & Hall, Boca Raton (2006)

    Book  Google Scholar 

  2. Baresi, L., Pasquale, L., Spoletini, P.: Fuzzy goals for requirements-driven adaptation. In: 18th IEEE RE, Sydney, Australia, September 2010

    Google Scholar 

  3. Cailliau, A., van Lamsweerde, A.: Handling knowledge uncertainty in risk-based requirements engineering. In: 23rd RE, Ottawa, Canada (2015)

    Google Scholar 

  4. Cavalcante, E., Quilbeuf, J., Traonouez, L.-M., Oquendo, F., Batista, T., Legay, A.: Statistical model checking of dynamic software architectures. In: Tekinerdogan, B., Zdun, U., Babar, A. (eds.) ECSA 2016. LNCS, vol. 9839, pp. 185–200. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-48992-6_14

    Chapter  Google Scholar 

  5. CPSoS: European Research and Innovation Agenda on Cyber-Physical Systems-of-Systems 2016–2025 (2016). http://www.cpsos.eu/roadmap/

  6. Esfahani, N., Malek, S.: Uncertainty in self-adaptive software systems. In: de Lemos, R., Giese, H., Müller, H.A., Shaw, M. (eds.) Software Engineering for Self-Adaptive Systems II. LNCS, vol. 7475, pp. 214–238. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-35813-5_9

    Chapter  Google Scholar 

  7. Tao, F., Zhang, M., Nee, A.Y.C.: Digital Twin Driven Smart Manufacturing. Academic Press, Cambridge (2019)

    Google Scholar 

  8. Garlan, D.: Software engineering in an uncertain world. In: ACM Future of Software Engineering Research, Santa Fe, NM, USA, November 2010

    Google Scholar 

  9. Grieves, M.: Virtually Perfect: Driving Innovative and Lean Products through Product Lifecycle Management. Space Coast Press, Cocoa Beach (2011)

    Google Scholar 

  10. Guessi, M., Oquendo, F., Nakagawa, E.Y.: Checking the architectural feasibility of systems-of-systems using formal descriptions. In: 11th IEEE SoSE, Kongsberg, Norway (2016)

    Google Scholar 

  11. Hubbard, D.W.: How to Measure Anything, 3rd edn. Wiley, Hoboken (2014)

    Google Scholar 

  12. INCOSE: SE Vision 2025 (2014). www.incose.org/AboutSE/sevision

  13. Jia, D., Lu, K., Wang, J., Zhang, X., Shen, X.: A survey on platoon-based vehicular cyber-physical systems. IEEE Commun. Surv. Tutor. 18(1), 263–284 (2016)

    Article  Google Scholar 

  14. Klein, J., van Vliet, H.: A systematic review of system-of-systems architecture research. In: 9th ACM QoSA, Vancouver, Canada, June 2013

    Google Scholar 

  15. Maier, M.W.: Architecting principles for systems-of-systems. Syst. Eng. J. 1(4), 267–284 (1998)

    Article  Google Scholar 

  16. Milner, R.: Communicating and Mobile Systems: The π-Calculus. Cambridge Press, Cambridge (1999)

    MATH  Google Scholar 

  17. Olarte, C., Rueda, C., Valencia, F.D.: Models and emerging trends of concurrent constraint programming. Int. J. Constraints 18, 535–578 (2013)

    Article  MathSciNet  Google Scholar 

  18. OMG: Precise Semantics for Uncertainty Modeling, Request For Proposal, OMG Document ad/2017-12-01, December 2017

    Google Scholar 

  19. Oquendo, F.: Formally describing the software architecture of systems-of-systems with SosADL. In: 11th IEEE SoSE, Kongsberg, Norway, June 2016

    Google Scholar 

  20. Oquendo, F.: The π-calculus for SoS: novel π-calculus for the formal modeling of software-intensive systems-of-systems. In: Communicating Process Architectures (CPA), vol. 69 (2016)

    Google Scholar 

  21. Oquendo, F.: Case study on formally describing the architecture of a software-intensive system-of-systems with SosADL. In: 15th IEEE SMC, Budapest, Hungary, October 2016

    Google Scholar 

  22. Oquendo, F.: Formally describing the architectural behavior of software-intensive systems-of-systems with SosADL. In: 21st IEEE ICECCS, Dubai, UAE, November 2016

    Google Scholar 

  23. Oquendo, F.: Software architecture challenges and emerging research in software-intensive systems-of-systems. In: Tekinerdogan, B., Zdun, U., Babar, A. (eds.) ECSA 2016. LNCS, vol. 9839, pp. 3–21. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-48992-6_1

    Chapter  Google Scholar 

  24. Oquendo, F.: Architecturally describing the emergent behavior of software-intensive system-of-systems with SosADL. In: 12th IEEE SoSE, Waikoloa, Hawaii, USA, June 2017

    Google Scholar 

  25. Oquendo, F.: Formally describing self-organizing architectures for systems-of-systems on the internet-of-things. In: Cuesta, C.E., Garlan, D., Pérez, J. (eds.) ECSA 2018. LNCS, vol. 11048, pp. 20–36. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-00761-4_2

    Chapter  Google Scholar 

  26. Oquendo, F.: Coping with uncertainty in systems-of-systems architecture modeling. In: 14th IEEE SoSE, Anchorage, Alaska, USA, May 2019

    Google Scholar 

  27. Oquendo, F., Buisson, J., Leroux, E., Moguérou, G., Quilbeuf, J.: The SosADL architect studio. In: SiSoS 2016, Copenhagen, DK. ACM, November 2016

    Google Scholar 

  28. Oquendo, F., Buisson, J., Leroux, E., Moguérou, G.: A formal approach for architecting software-intensive systems-of-systems with guarantees. In: 13th IEEE SoSE, Paris, France, June 2018

    Google Scholar 

  29. Oxford Dict. https://en.oxforddictionaries.com/definition/uncertainty

  30. Quilbeuf, J., Cavalcante, E., Traonouez, L.-M., Oquendo, F., Batista, T., Legay, A.: A logic for the statistical model checking of dynamic software architectures. In: Margaria, T., Steffen, B. (eds.) ISoLA 2016. LNCS, vol. 9952, pp. 806–820. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-47166-2_56

    Chapter  Google Scholar 

  31. Reynolds, C.W.: Flocks, herds, and schools: a distributed behavioral model, in computer graphics. In: 14th SIGGRAPH, Anaheim, USA (1987)

    Google Scholar 

  32. Roca, D., Nemirovsky, D., Nemirovsky, M., Milito, R., Valero, M.: Emergent behaviors in the internet-of-things: the ultimate ultra-large-scale system. In: IEEE Micro, vol. 36, no. 6, November–December 2016

    Google Scholar 

  33. Thunnissen, D.P.: Uncertainty classification for the design and development of complex systems. In: 3rd Predictive Methods Conference (PMC), Newport Beach, CA, USA, June 2003

    Google Scholar 

  34. Whittle, J., Sawyer, P., Bencomo, N., Cheng, B.H.C., Bruel, J.-M.: RELAX: a language to address uncertainty in self-adaptive systems requirement. Requir. Eng. J. 15(2), 177–196 (2010)

    Article  Google Scholar 

  35. Zhang, M., Selic, B., Ali, S., Yue, T., Okariz, O., Norgren, R.: Understanding uncertainty in cyber-physical systems: a conceptual model. In: Wąsowski, A., Lönn, H. (eds.) ECMFA 2016. LNCS, vol. 9764, pp. 247–264. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-42061-5_16

    Chapter  Google Scholar 

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Oquendo, F. (2019). Dealing with Uncertainty in Software Architecture on the Internet-of-Things with Digital Twins. In: Misra, S., et al. Computational Science and Its Applications – ICCSA 2019. ICCSA 2019. Lecture Notes in Computer Science(), vol 11619. Springer, Cham. https://doi.org/10.1007/978-3-030-24289-3_57

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  • DOI: https://doi.org/10.1007/978-3-030-24289-3_57

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