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Conference Papers Year : 2017

Design Framework for Reliable Multiple Autonomic Loops in Smart Environments


Today's control systems such as smart environments have the ability to adapt to their environment in order to achieve a set of objectives (e.g., comfort, security and energy savings). This is done by changing their behaviour upon the occurrence of specific events. Building such a system requires to design and implement autonomic loops that collect events and measurements, make decisions and execute the corresponding actions. The design and the implementation of such loops are made difficult by several factors: the complexity of systems with multiple objectives, the risk of conflicting decisions between multiple loops, the inconsistencies that can result from communication errors and hardware failures and the heterogeneity of the devices. In this paper, we propose a design framework for reliable and self-adaptive systems, where multiple autonomic loops can be composed into complex managers, and we consider its application to smart environments. We build upon the proposed framework a generic autonomic loop which combines an automata-based controller that makes correct and coherent decisions, a transac-tional execution mechanism that avoids inconsistencies, and an abstraction layer that hides the heterogeneity of the devices. We propose patterns for composition of such loops, in parallel, coordinated, and hierarchically, with benefits from the leveraging of automata-based modular constructs, that provides for guarantees on the correct behaviour of the controlled system. We implement our framework with the transactional middleware LINC, the reactive language Heptagon/BZR and the abstraction framework PUTUTU. A case study in the field of building automation is presented to illustrate the proposed framework.
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cea-01570026 , version 1 (28-07-2017)


  • HAL Id : cea-01570026 , version 1


Adja Ndeye Sylla, Maxime Louvel, Eric Rutten, Gwenaël Delaval. Design Framework for Reliable Multiple Autonomic Loops in Smart Environments. 2017 IEEE International Conference on Cloud and Autonomic Computing (ICCAC), Sep 2017, Tucson, AZ, United States. ⟨cea-01570026⟩
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