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IAS: an IoT Architectural Self-adaptation Framework

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Abstract

This paper develops a generic approach to model control loops and their interac- tion 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 trans- mission system. This industrial use-case is a part of CPS4EU European industrial innovation pro ject.
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Dates and versions

hal-02900674 , version 1 (16-07-2020)

Identifiers

  • HAL Id : hal-02900674 , version 1

Cite

Mahyar T Moghaddam, Eric Rutten, Philippe Lalanda, Guillaume Giraud. IAS: an IoT Architectural Self-adaptation Framework. ECSA 2020 - 14th European Conference on Software Architecture, Sep 2020, L’Aquila, Italy. pp.1-16. ⟨hal-02900674⟩
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