Mobility Data Pattern Tracking via Multidimensional Data View Approach

Many recent research work showed the importance of mobility data pattern tracking in mobile telecommunication systems since many mobile tracking and locating strategies depend on the accuracy of real-time mobility data in mobile data management systems. In order to support different knowledge based mobile tracking and locating strategies, the mobile data management system must dynamically and adaptively maintain the mobility data patterns such as traffic density and peaks along different dimensions such as time, cells and others. In this paper, we will present a multidimensional approach to keep track of the frequently updated mobility data. Our approach employs an adaptive multidimensional histogram to do the followings: 1. adaptively adjusting the resolution of mobility data patterns from multidimensional point of view; 2. accurately tracking the real-time mobility data patterns (knowledge) with high resolution.