Abstract
This paper develops a generic approach to model control loops and their interaction within the Internet of Things (IoT) environments. We take advantage of MAPE-K loops to enable architectural self-adaptation. The system’s architectural setting is aligned with the adaptation goals and the components run-time situation and constraints. We introduce an integrated framework for IoT Architectural Self-adaptation (IAS) where functional control elements are in charge of environmental adaptation and autonomic control elements handle the functional system’s architectural adaptation. A Queuing Networks (QN) approach was used for modeling the IAS. The IAS-QN can model control levels and their interaction to perform both architectural and environmental adaptations. The IAS-QN was modeled on a smart grid system for the Melle-Longchamp area (France). Our architectural adaptation approach successfully set the propositions to enhance the performance of the electricity transmission system. This industrial use-case is a part of CPS4EU European industrial innovation project (CPS4EU is a three years project funded by the H2020-ECSEL-2018-IA. The project develops four vital IoT technologies, namely computing, connectivity, sensing, and cooperative systems. It incorporates those IoT technologies through pre-integrated architectures and design tools. It instantiates the architectures in dedicated use-cases from a strategic application viewpoint for automotive, smart grid, and industrial automation https://cps4eu.eu).
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Notes
- 1.
Electricity Transmission Network, usually known as RTE, is the electricity transmission system operator of France.
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Moghaddam, M.T., Rutten, E., Lalanda, P., Giraud, G. (2020). IAS: An IoT Architectural Self-adaptation Framework. In: Jansen, A., Malavolta, I., Muccini, H., Ozkaya, I., Zimmermann, O. (eds) Software Architecture. ECSA 2020. Lecture Notes in Computer Science(), vol 12292. Springer, Cham. https://doi.org/10.1007/978-3-030-58923-3_22
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