1 Department of Computer Science, Faculty of Science, Aarhus University, Aarhus University2 Department of Computer Science, Science and Technology, Aarhus University3 Department of Computer Science, Science and Technology, Aarhus University
Self-management for pervasive middleware is important to realize the Ambient Intelligence vision. In this paper, we present an OWL/SWRL context ontologies based self-management approach for pervasive middleware where OWL ontology is used as means for context modeling. The context ontologies are incorporating the dynamic context information, including device and service run time information, which can then be used for running status checking and diagnosis, QoS monitoring, and further to achieve other self-management features, such as the self-conﬁguration and self-adaptation. We demonstrate the OWL/SWRL context ontologies based self-management approach with the self-diagnosis in Hydra middleware, using device state machine and other dynamic context information, for example web service calls. The evaluations in terms of extensibility, performance and scalability show that this approach is eﬀective in pervasive service environment.
Fifth International Workshop on Modelling and Reasoning in Context. Proceedings, 2008
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Fifth International Workshop on Modelling and Reasoning in Context. MRC 2008