J. Tsiligaridis and R. Acharya (USA)
Data Mining, Mobile Computing, Collaborative Systems and Applications, Distributed computing.
The problem of server performance in a contemporary, rapidly developed and multi-discipline environment is examined. The administration of the data sources or repositories during the execution of the query plan becomes primary interest especially for starting the query server. A collaborative system between nodes, Base Stations (BSs) and servers is developed and. a new query processing method, based on group and query prediction mobility (GQM) with Data Mining techniques is proposed. Our new approach for GQM with the Merge Itemset Algorithm (MIA) can guarantee the “prefetch” operation for the users so that their data will have already been waiting for them in their next appropriate cell. Moreover, new metrics for external queries (queries not completed in the starting servers) estimate the dependency among servers. Finally the server decides for the query decomposition plan including replication schemes, for a group of users so that the data be sent directly to their last cell; diminishing their dependency on communications and seeking additional resources. This new integrated approach can contribute a lot to the server’s independent or semi autonomous work. Simulation results are provided.
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