An Ontology-based Context Model in Intelligent Environments
This work addresses the problem of lacking infrastructure support for context-aware applications in dynamic environments, but it appears incremental as it builds on existing ontology and middleware approaches without claiming major breakthroughs.
The authors tackled the complexity of building context-aware systems in intelligent environments by proposing a formal ontology-based context model using OWL, which enables semantic representation, reasoning, and knowledge sharing, and they also introduced a Service-Oriented Context-Aware Middleware (SOCAM) architecture for developing context-aware services.
Computing becomes increasingly mobile and pervasive today; these changes imply that applications and services must be aware of and adapt to their changing contexts in highly dynamic environments. Today, building context-aware systems is a complex task due to lack of an appropriate infrastructure support in intelligent environments. A context-aware infrastructure requires an appropriate context model to represent, manipulate and access context information. In this paper, we propose a formal context model based on ontology using OWL to address issues including semantic context representation, context reasoning and knowledge sharing, context classification, context dependency and quality of context. The main benefit of this model is the ability to reason about various contexts. Based on our context model, we also present a Service-Oriented Context-Aware Middleware (SOCAM) architecture for building of context-aware services.