Modeling and specifying formally compound MAPE pattern for self-adaptive IoT systems

IoT systems are required to manage themselves to changes regarding their internal and external contexts. So, adaptability is a very important aspect in IoT software systems. The MAPE (Monitoring, Analysis, Planning, Execution) control loop model, inspired from the autonomic nervous system, has been...

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Bibliographic Details
Published in:Innovations in systems and software engineering 2022-12, Vol.18 (4), p.505-521
Main Authors: Hachicha, Marwa, Ben Halima, Riadh, Hadj Kacem, Ahmed
Format: Article
Language:English
Subjects:
Adaptation
Adaptive control
Adaptive systems
Architecture
Artificial Intelligence
Autonomic nervous system
Composition
Computer Applications
Computer Science
Decentralized control
Fall detection
Formal specifications
Modelling
S.i. : Detect 2020
Self adaptive control systems
Software Engineering
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Summary:IoT systems are required to manage themselves to changes regarding their internal and external contexts. So, adaptability is a very important aspect in IoT software systems. The MAPE (Monitoring, Analysis, Planning, Execution) control loop model, inspired from the autonomic nervous system, has been identified as a crucial element for realizing self-adaptation in software systems. In fact, software design patterns provide architects and developers with reusable software elements helping them to master building complex software systems including several interconnected components. Complex self-adaptive systems require several architectural patterns in their design which leads to the need of architectural pattern composition. In this paper, we focus in modeling adaptability in IoT systems through a set of MAPE design patterns for decentralized control in self-adaptive systems and we propose an approach for composing them using a UML profile. Then, we propose formalizing the composition process using the Event-B method. In addition, we propose verifying adaptation properties based on the resulting formal specification. We illustrate our approach by modeling structural and behavioral features of the hybrid pattern resulting from the composition of two MAPE patterns and applied to the fall-detection ambient assisting living system for elderly people.
ISSN:1614-5046
1614-5054
DOI:10.1007/s11334-021-00409-3