lnu.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • 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). KU 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: 2019-09-03Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records BETA

Weyns, Danny

Search in DiVA

By author/editor
Weyns, Danny
By organisation
Department of computer science and media technology (CM)
Software Engineering

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 3 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • 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