In smart living spaces, a reliable context-aware application must adapt to the variable environment and should function to complete the user's requirements. Therefore, if a context-aware application is to achieve the user's requirements smoothly, it must understand the environment status according to trustworthy context information. However, the context information influenced by the environment status may be imperfect. If a context-aware application responds to the user's requirements using the incorrect context information, this will lead to undesirable result. To resolve these problems, this paper proposes a context model (CM) to evaluate the reliability of context information and predicted the context information that context-aware application needs. When CM approves of the context information, it considers both the key features of context information, and also the different requirements of the context-aware application. Finally, an experiment is proposed to verify the reliability of CM. The experiment verifies that the reliability of context information recommended by CM can represent the real status. In addition, the experiment verifies whether CM can provide appropriate context information according to the particular requirements of a context-aware application.
[1]
Julie A. McCann,et al.
Adaptive middleware for context-aware applications in smart-homes
,
2004,
MPAC '04.
[2]
Maria Ebling,et al.
The design and applications of a context service
,
2002,
MOCO.
[3]
Shing-Chi Cheung,et al.
Inconsistency detection and resolution for context-aware middleware support
,
2005,
ESEC/FSE-13.
[4]
Peter Steenkiste,et al.
Providing contextual information to pervasive computing applications
,
2003,
Proceedings of the First IEEE International Conference on Pervasive Computing and Communications, 2003. (PerCom 2003)..
[5]
Jian Lu,et al.
Rewards-based negotiation for providing context information
,
2006,
MPAC '06.
[6]
Jadwiga Indulska,et al.
Modelling and using imperfect context information
,
2004,
IEEE Annual Conference on Pervasive Computing and Communications Workshops, 2004. Proceedings of the Second.