Association rule mining and load balancing strategy in grid systems

The parallel and distributed systems represent one of the important solutions proposed to ameliorate the performance of the sequential association rule mining algorithms. However, parallelization and distribution process is not trivial and still facing many problems of synchronization, communication, and workload balancing. Our study is limited to the workload balancing problem. In this paper, we propose a dynamic load balancing strategy of association rule mining algorithm under a grid environment. This strategy is built upon a hierarchical grid model with three levels: Super coordinator, coordinator, and processing nodes. The main objective of our strategy is to ameliorate the performances of the distributed association rule mining algorithm “APRIORI”.