Mobility Prediction of Mobile Users in Mobile Environment Using Knowledge Grid

In this paper, we propose a new distributed algorithm named KMPM (Knowledge Grid Based Mobility Pattern Mining) for mining next location of a mobile user in a Personal Communication Systems (PCS) network. The moving logs of mobile users in mobile computing environment are stored in the grid node located in different locations. The generated moving logs are used for mining mobility patterns in a mobile computing system. The discovered location patterns can be used to provide various location based services to the mobile user by the application server in mobile computing environment. Data grid provides geographically distributed database for Computational Grid which implements (Knowledge Grid based Mobility Pattern Mining) KMPM algorithm. We built data grid system on a cluster of workstation using open source Globus Toolkit4.0 and Message Passing Interface extended with Grid Services (MPICH-G2). The experiments were conducted on different configurations and the computation time was recorded for each operation. We compared our result with various grid configurations and it shows a very good speedup.