Abstract
In this paper, we propose a restoration scheme from the location server failure using mobile user's location pattern prediction. We consider each user has its own movement pattern with a day, a week, or a month. Whenever a mobile user registers or updates its location, the movement pattern is learned by a neuro-fuzzy inference system (NFS). When a failure occurs, the locations of mobile users are predicted by the NFS, and the predicted location is used to find the location where mobile user is. We classify several mobility patterns for individuals, and the performance of the NFS prediction and the restoration scheme is shown through simulation.
This work was supported by MIC(Ministry of Information and Communications).
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© 1999 Springer-Verlag Berlin Heidelberg
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Park, C.Y., Gil, JM., Han, YH., Hwang, CS. (1999). Failure restoration for location server with user movement learning and prediction. In: Polychronopoulos, C., Fukuda, K.J.A., Tomita, S. (eds) High Performance Computing. ISHPC 1999. Lecture Notes in Computer Science, vol 1615. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0094942
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DOI: https://doi.org/10.1007/BFb0094942
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