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Model-driven Engineering of Decentralized Control in Cyber-Physical Systems
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM), Department of Computer Science.ORCID iD: 0000-0002-2935-6583
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM), Department of Computer Science.ORCID iD: 0000-0001-6981-0966
University of Rome 'Tor Vergata', Italy.
2017 (English)In: Proceedings of the 2nd International Workshop onĀ  Foundations and Applications of Self* Systems (FAS*W), IEEE, 2017, p. 7-12Conference paper, Published paper (Refereed)
Abstract [en]

Self-Adaptation is nowadays recognized as an effective approach to manage the complexity and dynamics inherent to cyber-physical systems, which are composed of deeply intertwined physical and software components interacting with each other. A self-Adaptive system typically consists of a managed subsystem and a managing subsystem that implements the adaptation logic by means of the well established MAPE-K control loop. Since in large distributed settings centralized control is hardly adequate to manage the whole system, self-Adaptation should be achieved through collective decentralized control, that is multiple cyber-physical entities must adapt in order to address critical runtime conditions. Developing such systems is challenging, as several dimensions concerning both the cyber-physical system and the decentralized control loop should be considered. To this end, we promote MAPE-K components as first-class modeling abstractions and provide a framework supporting the design, development, and validation of decentralized self-Adaptive cyber-physical systems.

Place, publisher, year, edition, pages
IEEE, 2017. p. 7-12
Keywords [en]
Collective Adaptive Systems; Cyber-Physical Systems; Decentralized Control; Framework; MAPE-K loop; Self-Adaptive Systems
National Category
Robotics Computer Vision and Robotics (Autonomous Systems)
Research subject
Computer Science, Software Technology
Identifiers
URN: urn:nbn:se:lnu:diva-67530DOI: 10.1109/FAS-W.2017.113ISI: 000426936100002ISBN: 9781509065585 (print)OAI: oai:DiVA.org:lnu-67530DiVA, id: diva2:1137131
Conference
Self-Adaptive and Self-Organizing Systems (SASO), September 18-22, 2017, Tucson
Available from: 2017-08-30 Created: 2017-08-30 Last updated: 2018-03-22Bibliographically approved

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D'Angelo, MirkoCaporuscio, Mauro

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CiteExportLink to record
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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
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