lnu.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Patterns for self-adaptation in Cyber-Physical Systems
Technische Universität Wien, Austria.
Technische Universität Wien, Austria.
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM), Department of Computer Science. Katholieke Univ Leuven, Belgium.ORCID iD: 0000-0002-1162-0817
Charles University Prague, Czechia.
Show others and affiliations
2017 (English)In: Multi-Disciplinary Engineering for Cyber-Physical Production Systems: Data Models and Software Solutions for Handling Complex Engineering Projects, Springer, 2017, p. 331-368Chapter in book (Other academic)
Abstract [en]

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. © Springer International Publishing AG 2017.

Place, publisher, year, edition, pages
Springer, 2017. p. 331-368
Keywords [en]
Collective intelligence systems, Cyber-physical systems, Patterns, Self-adaptation, Software architecture, Systematic study
National Category
Software Engineering
Research subject
Computer Science, Software Technology
Identifiers
URN: urn:nbn:se:lnu:diva-85051DOI: 10.1007/978-3-319-56345-9_13Scopus ID: 2-s2.0-85048914233ISBN: 9783319563459 (electronic)ISBN: 9783319563442 (print)OAI: oai:DiVA.org:lnu-85051DiVA, id: diva2:1336973
Note

Export Date: 11 June 2019; Book Chapter

Available from: 2019-07-11 Created: 2019-07-11 Last updated: 2025-06-25Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Weyns, Danny

Search in DiVA

By author/editor
Weyns, Danny
By organisation
Department of Computer Science
Software Engineering

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 113 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf