A dynamic load balancing strategy for generating association rule mining under a grid environment

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. In this paper we limited our study to the workload balancing problem. In this paper we propose a dynamic load balancing strategy of association rule mining algorithm under an environment of a grid. This strategy is built upon a hierarchical grid model with three levels "Super Coordinator, Coordinator, processing nodes". The main objective of our strategy is to reduce the complexity of the distributed association rule mining algorithms.