Email: marian.daun@thws.de
Email: jenniferbrings@gmail.com
Email: linda.feeken@dlr.de
Revised 28 March 2024
Accepted 2 April 2024
Available Online 18 April 2024
- DOI
- https://doi.org/10.55060/j.jseas.240418.001
- Keywords
- Goal modeling
GRL
Cyber-physical systems
System of systems
Adaptation planning - Abstract
Collaborative systems such as cyber-physical systems (CPS) dynamically form runtime networks to achieve goals that cannot be achieved by the individual system alone. While much research has been done on architectures for adaptive systems, these approaches do not consider the fact that goals exist on network level and thus need specific adaptation strategies. In decentralized settings where there is no central mechanism for orchestrating and coordinating the collaboration between systems, failure to adapt individual systems’ behaviors without considering the network’s overall outcome may result in a functional degradation of the entire network, possibly to the point of injuring humans and harming individual systems in the network. In this article, we propose a goal-based adaptation approach that takes the goals of the individual systems as well as the goals of the overall network into account. Our approach allows considering adaptation strategies based on the network goals which are fulfilled by automated behavioral adaptations of the individual system of the network. Results from a proof-of-concept application to an industrial case example show applicability and usefulness of the approach.
- Copyright
- © 2024 The Authors. Published by Athena International Publishing B.V.
- Open Access
- This is an open access article distributed under the CC BY-NC 4.0 license (https://creativecommons.org/licenses/by-nc/4.0/).
Cite This Article
TY - JOUR AU - Marian Daun AU - Bastian Tenbergen AU - Torsten Bandyszak AU - Jennifer Brings AU - Linda Feeken PY - 2024 DA - 2024/04/18 TI - Adaptation Strategy Planning for Collaborative Cyber-Physical Systems Using Goal Models JO - Journal of Software Engineering for Autonomous Systems SN - 2949-9372 UR - https://doi.org/10.55060/j.jseas.240418.001 DO - https://doi.org/10.55060/j.jseas.240418.001 ID - Daun 2024 ER -