Efficient location prediction in mobile cellular networks

Anagnostopoulos, T., Anagnostopoulos, C. and Hadjiefthymiades, S. (2012) Efficient location prediction in mobile cellular networks. International Journal of Wireless Information Networks, 19(2), pp. 97-111. (doi:10.1007/s10776-011-0166-9)

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Abstract

Mobile context-aware applications are capable of predicting the context of the user in order to operate pro-actively and provide advanced services. We propose an efficient spatial context classifier and a short-term predictor for the future location of a mobile user in cellular networks. We introduce different variants of the considered location predictor dealing with location (cell) identifiers and directions. Symbolic location classification is treated as a supervised learning problem. We evaluate the prediction efficiency and accuracy of the proposed predictors through synthetic and real-world traces and compare our solution with existing algorithms for location prediction. Our findings are very promising for the location prediction problem and the adoption of proactive context-aware applications and services.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Anagnostopoulos, Dr Christos
Authors: Anagnostopoulos, T., Anagnostopoulos, C., and Hadjiefthymiades, S.
College/School:College of Science and Engineering > School of Computing Science
Journal Name:International Journal of Wireless Information Networks
ISSN:1068-9605
ISSN (Online):1572-8129

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