Mobility prediction using future knowledge

Authors:
Michael H. Sun;Douglas M. Blough
Affiliations:
Georgia Institute of Technology, Atlanta, GA;Georgia Institute of Technology, Atlanta, GA
Venue:
Proceedings of the 10th ACM Symposium on Modeling, analysis, and simulation of wireless and mobile systems
Year:
2007

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Abstract

Anticipating user mobility can be a critical feature for today's mobile systems. We introduce a novel location predictor which incorporates knowledge of a user's potential future locations to improve prediction accuracy. Such future knowledge is often available through contextual sources such as a user's calendar, e-mail, or instant messaging conversations. Simulation results show that our future knowledge leveraging location predictor can improve prediction accuracy by 3% to 95% over history-only Markov predictors, depending on the amount of future knowledge that is available and the type of mobility exhibited by users.