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Multi-Disciplinary Engineering for Cyber-Physical Production Systems pp 331–368Cite as

Patterns for Self-Adaptation in Cyber-Physical Systems

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Abstract

Engineering Cyber-Physical Systems (CPS) is challenging, as these systems have to handle uncertainty and change during operation. A typical approach to deal with uncertainty is enhancing the system with self-adaptation capabilities. However, realizing self-adaptation in CPS, and consequently also in Cyber-Physical Production Systems (CPPS) as a member of the CPS family, is particularly challenging due to the specific characteristics of these systems, including the seamless integration of computational and physical components, the inherent heterogeneity and large-scale of such systems, and their open-endedness.

In this chapter we survey CPS studies that apply the promising design strategy of combining different self-adaptation mechanisms across the technology stack of the system. Based on the survey results, we derive recurring adaptation patterns that structure and consolidate design knowledge. The patterns offer problem-solution pairs to engineers for the design of future CPS and CPPS with self-adaptation capabilities. Finally, the chapter outlines the potential of collective intelligence systems for CPPS and their engineering based on the survey results.

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Notes

  1. 1.

    http://www.facebook.com/ (last visited 01/15/2017).

  2. 2.

    http://www.wikipedia.org/ (last visited 01/15/2017).

  3. 3.

    http://www.youtube.com/ (last visited 01/15/2017).

  4. 4.

    http://www.yelp.com/ (last visited 01/15/2017).

  5. 5.

    If the reader is familiar with this research method, this section can be skipped.

  6. 6.

    Supplementary material of the study is available at: http://qse.ifs.tuwien.ac.at/ci/material/pub/mde-cpps17/

  7. 7.

    Supplementary material of the study is available at: http://qse.ifs.tuwien.ac.at/ci/material/pub/mde-cpps17/

  8. 8.

    Supplementary material of the study is available at: http://qse.ifs.tuwien.ac.at/ci/material/pub/mde-cpps17/

  9. 9.

    http://www.waze.com/ (last visited 01/15/2017).

  10. 10.

    http://www.yelp.com/ (last visited 01/15/2017).

  11. 11.

    http://www.facebook.com (last visited 01/15/2017).

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Acknowledgements

This work was supported by the Christian Doppler Forschungsgesellschaft, the Federal Ministry of Science, Research and Economy, the National Foundation for Research, Technology and Development in Austria, and Technische Universität Wien research funds.

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Authors and Affiliations

  1. Institute of Software Technology and Interactive Systems, Technische Universität Wien, Wien, Austria

    Angelika Musil & Juergen Musil

  2. Department of Computer Science, KU Leuven, Leuven, Belgium

    Danny Weyns

  3. Department of Computer Science, Linnaeus University, Växjö, Sweden

    Danny Weyns

  4. Department of Distributed and Dependable Systems, Charles University Prague, Prague, Czechia

    Tomas Bures

  5. DISIM Department, University of L’Aquila, L’Aquila, Italy

    Henry Muccini & Mohammad Sharaf

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  1. Angelika Musil
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Correspondence to Angelika Musil .

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Editors and Affiliations

  1. Institute of Software Technology and Interactive Systems, Technische Universität Wien, Wien, Austria

    Stefan Biffl

  2. Institute of Ergonomics, Manufacturing Systems and Automation (IAF), Otto von Guericke University Magdeburg, Magdeburg, Germany

    Arndt Lüder

  3. Institute of Engineering Design and Logistics Engineering, Technische Universität Wien, Wien, Austria

    Detlef Gerhard

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Musil, A., Musil, J., Weyns, D., Bures, T., Muccini, H., Sharaf, M. (2017). Patterns for Self-Adaptation in Cyber-Physical Systems. In: Biffl, S., Lüder, A., Gerhard, D. (eds) Multi-Disciplinary Engineering for Cyber-Physical Production Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-56345-9_13

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