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Thuy Van T. Duong, Dinh Que Trany, Modeling mobility in wireless network with spatiotemporal state, East-West Journal of Mathematics, a special issue, vol 13 (2012), pp. 1-13 (fulltext)

In the wireless network, mobile users often change their accessing points to Internet. Then, while the mobile node transfers communica- tion from one access point to another access point - called handover or hando , it is not able to send or receive data. Predicting mobility is one of the prominent solutions for reducing the handover latency. Sev- eral approaches to the prediction have been considered such as Hidden Markov models, machine learning, data mining and so on. The data min- ing approach investigates the log le of node mobility history to predict its next move. In such a context, the spatial attributes of a mobile node are changing over time, and therefore time constraints between mobile locations play an crucial role. However, the current studies on mobility prediction are not satisfactory since spatial and temporal attributes of data are not considered simultaneously.

In this paper, we introduce a formal model of mobility based on spatial and temporal attributes of data in the wireless network. Based on this model, we construct mobility patterns and weighted mobility rules and then develop algorithms for discovering these patterns and rules.

Key words: mobitity modeling, mobility prediction, pattern, rule, spatiotemporality. 2000 AMS Mathematics Subject Classi cation: Applied Mathematics