Situation-Driven Multi-Purpose Adaptation in the Web of Things

Tracking #: 2086-3299

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Mehdi Terdjimi
Lionel Médini
Michael Mrissa1

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Guest Editors Sensors Observations 2018

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Full Paper
Existing adaptation solutions for Web of Things (WoT) applications are tightly coupled with application domains. We propose a generic solution that relies on Semantic Web standards to make adaptation decisions for various concerns, using contextual information. We formalize multi-purpose adaptation rules to infer and rank adaptation possibilities. We propose meta-rules to construct situation-driven sets of adaptation rules at application design time. As such, we propose a multi-layered theoretical framework that reduces the number of rules to produce coherent sets of adaptation decisions in various situations. We evaluate the correctness and coverage of this framework on a sustainable agriculture scenario.
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