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Self-Aware Model-Driven Pervasive Systems

Abstract : In pervasive computing vision, everyday objects are merged with small computers. They are immersed in heterogeneous and dynamic environments. As independent systems can interact with the same environment, it is hard to avoid conflicts. By identifying systems' objectives, capabilities and influences, and by reasoning about it, self-awareness may be the key to enable their collaboration. We aim to clarify definitions of self-awareness and related notions within pervasive computing, and to design one way to use it for pervasive systems collaboration. Different types of models and actual use cases will be implemented on iCasa pervasive platform to evaluate the relevance of the approach.
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https://hal.archives-ouvertes.fr/hal-01512679
Contributor : Eva Gerbert-Gaillard <>
Submitted on : Monday, April 24, 2017 - 11:20:52 AM
Last modification on : Monday, April 20, 2020 - 10:10:03 AM

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Gerbert-Gaillard Eva, Philippe Lalanda. Self-Aware Model-Driven Pervasive Systems. 2016 IEEE International Conference on Autonomic Computing (ICAC), Jul 2016, Wuerzburg, Germany. ⟨10.1109/ICAC.2016.26⟩. ⟨hal-01512679⟩

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