期刊名称：International Journal of Grid and Distributed Computing
印刷版ISSN：2005-4262
出版年度：2012
卷号：5
期号：4
出版社：SERSC
摘要：Mining association rules refers to extracting useful knowledge from large databases. Algo-rithms of this technique are both data and computation-intensive, which make grid platformsvery attractive for them. However, to exploit these platforms, new data partitioning featuresare required where the specificities of both association rule mining technique and grids mustbe taken into consideration.In this paper, we propose a novel data partitioning approach for distributed associationrule mining algorithms in the context of a grid computing environment. We conduct exper-iments using the French research grid "Grid'5000". Experimental results confirm that ourdata partitioning approach is very su.cient for balancing the load when homogeneous clus-ters are used. For heterogeneous clusters, the proposed data partitioning approach constitutethe preprocessing phase of the process of dynamic load balancing of distributed associationrule mining
关键词：Grid platforms; distributed association rule mining; data partitioning; work-;load balancing.
