Gal Badishi, Idit Keidar, et al.
IEEE TDSC
Development of context-aware applications is inherently complex. These applications adapt to changing context information: physical context, computational context, and user context/tasks. Context information is gathered from a variety of sources that differ in the quality of information they produce and that are often failure prone. The pervasive computing community increasingly understands that developing context-aware applications should be supported by adequate context information modelling and reasoning techniques. These techniques reduce the complexity of context-aware applications and improve their maintainability and evolvability. In this paper we discuss the requirements that context modelling and reasoning techniques should meet, including the modelling of a variety of context information types and their relationships, of high-level context abstractions describing real world situations using context information facts, of histories of context information, and of uncertainty of context information. This discussion is followed by a description and comparison of current context modelling and reasoning techniques and a lesson learned from this comparison. © 2009 Elsevier B.V. All rights reserved.
Gal Badishi, Idit Keidar, et al.
IEEE TDSC
Matthias Kaiserswerth
IEEE/ACM Transactions on Networking
Elizabeth A. Sholler, Frederick M. Meyer, et al.
SPIE AeroSense 1997
Alfonso P. Cardenas, Larry F. Bowman, et al.
ACM Annual Conference 1975