TY - JOUR
T1 - Defining adaptivity and logical architecture for engineering (smart) self-adaptive cyber–physical systems
AU - Petrovska, Ana
AU - Kugele, Stefan
AU - Hutzelmann, Thomas
AU - Beffart, Theo
AU - Bergemann, Sebastian
AU - Pretschner, Alexander
N1 - Publisher Copyright:
© 2022 Elsevier B.V.
PY - 2022/7
Y1 - 2022/7
N2 - Context: Modern cyber–physical systems (CPSs) are embedded in the physical world and intrinsically operate in a continuously changing and uncertain environment or operational context. To meet their business goals and preserve or even improve specific adaptation goals, besides the variety of run-time uncertainties and changes to which the CPSs are exposed—the systems need to self-adapt. Objective: The current literature in this domain still lacks a precise definition of what self-adaptive systems are and how they differ from those considered non-adaptive. Therefore, in order to answer how to engineer self-adaptive CPSs or self-adaptive systems in general, we first need to answer what is adaptivity, correspondingly self-adaptive systems. Method: In this paper, we first formally define the notion of adaptivity. Second, within the frame of the formal definitions, we propose a logical architecture for engineering decentralised self-adaptive CPSs that operate in dynamic, uncertain, and partially observable operational contexts. This logical architecture provides a structure and serves as a foundation for the implementation of a class of self-adaptive CPSs. Results: First, our results show that in order to answer if a system is adaptive, the right framing is necessary: the system's adaptation goals, its context, and the time period in which the system is adaptive. Second, we discuss the benefits of our architecture by comparing it with the MAPE-K conceptual model. Conclusion: Commonly accepted definitions of adaptivity and self-adaptive systems are necessary for work in this domain to be compared and discussed since the same terms are often used with different semantics. Furthermore, in modern self-adaptive CPSs, which operate in dynamic and uncertain contexts, it is insufficient if the adaptation logic is specified during the system's design, but instead, the adaptation logic itself needs to adapt and “learn” during run-time.
AB - Context: Modern cyber–physical systems (CPSs) are embedded in the physical world and intrinsically operate in a continuously changing and uncertain environment or operational context. To meet their business goals and preserve or even improve specific adaptation goals, besides the variety of run-time uncertainties and changes to which the CPSs are exposed—the systems need to self-adapt. Objective: The current literature in this domain still lacks a precise definition of what self-adaptive systems are and how they differ from those considered non-adaptive. Therefore, in order to answer how to engineer self-adaptive CPSs or self-adaptive systems in general, we first need to answer what is adaptivity, correspondingly self-adaptive systems. Method: In this paper, we first formally define the notion of adaptivity. Second, within the frame of the formal definitions, we propose a logical architecture for engineering decentralised self-adaptive CPSs that operate in dynamic, uncertain, and partially observable operational contexts. This logical architecture provides a structure and serves as a foundation for the implementation of a class of self-adaptive CPSs. Results: First, our results show that in order to answer if a system is adaptive, the right framing is necessary: the system's adaptation goals, its context, and the time period in which the system is adaptive. Second, we discuss the benefits of our architecture by comparing it with the MAPE-K conceptual model. Conclusion: Commonly accepted definitions of adaptivity and self-adaptive systems are necessary for work in this domain to be compared and discussed since the same terms are often used with different semantics. Furthermore, in modern self-adaptive CPSs, which operate in dynamic and uncertain contexts, it is insufficient if the adaptation logic is specified during the system's design, but instead, the adaptation logic itself needs to adapt and “learn” during run-time.
KW - Adaptivity
KW - Knowledge
KW - Logical architecture
KW - Quality function
KW - Self-adaptive cyber–physical systems
UR - http://www.scopus.com/inward/record.url?scp=85125527843&partnerID=8YFLogxK
U2 - 10.1016/j.infsof.2022.106866
DO - 10.1016/j.infsof.2022.106866
M3 - Article
AN - SCOPUS:85125527843
SN - 0950-5849
VL - 147
JO - Information and Software Technology
JF - Information and Software Technology
M1 - 106866
ER -