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


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2021-07-19

AUTHORS

Marwa Hachicha, Riadh Ben Halima, Ahmed Hadj Kacem

ABSTRACT

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. More... »

PAGES

1-17

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11334-021-00409-3

DOI

http://dx.doi.org/10.1007/s11334-021-00409-3

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1139800889


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