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A predictive location management scheme based on semi-random mobility model

Predictive location management schemes based on the user mobility patterns are preferred over non-predictive ones as the paging cost drastically decreases. In existing predictive schemes a MT is expected to be intelligent as it is assigned a lot of computation load which may otherwise be easily shared by the MSC. Furthermore some schemes require the regional route maps. We propose a predictive scheme which assigns more load to the MSC than MT. The MT stores only current day movement log and sends this log to MSC during night. The MSC computes the unique sub-patterns, and identifies hot cell, i.e. the last cell of the sub-patterns which is sent to the MT. The MT sends update when it leaves a hot cell which enables the MSC to identify the sub-pattern to be followed next. The MSC pages only a cell corresponding to the sub-pattern when call arrives. If not found pages a set of probable cells. An analytical study considering semi-random mobility model gives the total location management cost using the proposed scheme