An analysis of location management cost by predictive location update policy in mobile cellular networks

An analysis of location management cost by predictive location update policy in mobile cellular networks

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Article ID: iaor20091147
Country: South Korea
Volume: 34
Issue: 2
Start Page Number: 160
End Page Number: 171
Publication Date: Jun 2008
Journal: Journal of the Korean Institute of Industrial Engineers
Authors: , , ,
Keywords: location
Abstract:

MU's mobility patterns can be found from movement history data. The prediction accuracy and model complexity depend on the degree of application of history data. The more data we use, the more accurate the prediction is. As a result, the location management cost is reduced, but complexity of the model increases. In this paper, we classify MU's mobility patterns into four types. For each type, we find the respective optimal number of application of history data, and predictive location area by using the simulation. The optimal numbers of four types are shown to be different. When we use more than three applications of history data, the simulation time and data storage are shown to increase very steeply.

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