LeZi-update: an information-theoretic approach to track mobile users in PCS networks
MobiCom '99 Proceedings of the 5th annual ACM/IEEE international conference on Mobile computing and networking
Numerical Methods for Engineers: With Software and Programming Applications
Numerical Methods for Engineers: With Software and Programming Applications
A predictive location model for location-based services
GIS '03 Proceedings of the 11th ACM international symposium on Advances in geographic information systems
Enhanced path prediction for network resource management in wireless LANs
IEEE Wireless Communications
Predicting the location of mobile users: a machine learning approach
Proceedings of the 2009 international conference on Pervasive services
Extending context spaces theory by proactive adaptation
ruSMART/NEW2AN'10 Proceedings of the Third conference on Smart Spaces and next generation wired, and 10th international conference on Wireless networking
Formal verification of context and situation models in pervasive computing
Pervasive and Mobile Computing
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Mobile applications are required to operate in ubiquitous environments of dynamic nature. Specifically, the availability of resources and services may vary significantly during a typical session of system operation. As a consequence, mobile applications need to be capable of adapting to these changes to ensure the best possible level of service to the user. Therefore, such adaptive applications may have pre-evaluated the appropriate knowledge of their environment to act efficiently. Such knowledge is not known a priori, so information prediction and proactivity should enhance and extend the functionality of such applications in order to be adaptable to the future changes of their underlying computational environment. In this paper, we discuss and evaluate such a context prediction algorithm.