Hybrid reasoning in the CARE middleware for context-awareness

The Context Aggregation and REasoning (CARE) middleware aims at supporting context-aware adaptation of internet services in a mobile computing environment. Context awareness requires the acquisition, representation and processing of information that goes beyond raw context data – like device features, network status and user location – to include semantically rich data such as the current activity and interests of users. Representing and reasoning with the latter class of data require the use of ontologies and ontological reasoning. It is well known that reasoning with ontologies poses significant performance issues. The CARE hybrid reasoning mechanism is based on a loose interaction between ontological reasoning and efficient reasoning in a restricted logic programming language. In this paper we illustrate the hybrid reasoning approach adopted by CARE and report the extensive experimental results on ontology-based context reasoning that support our approach.