Research And Implementation Of Context Information Query, Subscription And Uncertainty Reasoning

With the growing popularity of computers and rapid development, as well as mobile computing and sensor networks, extraordinary development, a variety of mobile devices more and more into people's lives. The calculation is also integrated into people's lives. Ubiquitous Computing is the second new change after mainframe computing and desktop computing. Ubiquitous computing has been proposed changing the way of using computing resources. Computer-centric computing will be turned into human-centered computing. Pervasive computing model requires the user computing devices to sense the context information when it changes, and make the appropriate action. Pervasive computing is to create a people-oriented information service to the new environment. Context-aware computing is one of the key theories. Context-aware computing combines variety of computing resources, information services and human to maximize the implementation of user tasks automatically.This paper presents a new ontology-based framework for context-aware systems. The system is based middleware theory. It separated gathering context information and development of context-aware applications. The system shields the context of specific heterogeneity for context-aware applications and screens development of specific context-aware applications for various types of sensors. Thereby the system simplifies the processing of context information. This paper also provides two separate but coordinated ways to processing context information. These two processes are open to each other through the synchronous control mechanism, sharing context information. And this article selects SPARQL as the context information query language. Through the introduction of the workflow model, it's greatly simplifies application development for the context-aware application developers.The modeling and reasoning with uncertain context information is one of key problem of building context-aware applications in pervasive computing environment. In this paper, we proposed a method of modeling uncertainty contexts by combining the D-S theory with ontology model. And also an improved evidences combination rule is presented not only to solve the D-S theory limitations in the case of high-degree conflict evidences but also to make the reasoning has self-adaptive. Then we design and implement the uncertain reasoning algorithm. Finally, we verify the feasibility, rationality and effectiveness of this approach through the e-health use case of the prototype system.