A Data Allocation Scheme using Data Mining for Wireless Cellular Network

A centralized collaborative system between nodes, servers and Base Stations (BSs) is developed, and a new data allocation scheme based on group and query prediction mobility scheme with Data Mining techniques is proposed. With this approach we minimize the cost of remote access by reducing the number of network messages and improve the response time of the queries. A series of algorithms is developed so that the system can provide the "prefetch" operation for the group of users according to their mobility. The data have to follow the users’ moves. Our new approach contains Call Admission Control (CAC) with a prediction scheme for Group and Query Mobility (GQM) based on two phases: the Merge Itemsets Algorithm (MIA) and the one step dynamic Replication Algorithm (RAL1) respectively. The RAL1, providing two data replication policies, can guarantee the acceleration of the query execution. The proposed system can be used for site selection or reduction of the number of sites in query optimization, and also the design of any new architecture for distributed query processing. Simulation results are provided.