162-173 Dynamic Load Balancing for Parallel Association Rule Mining on Heterogenous PC Cluster Systems. The dynamic load balancing strategies for parallel association rule mining are proposed under heterogeneous PC cluster environment. PC cluster is recently regarded as one of the most promising platforms for heavy data intensive applications, such as decision support query processing and data mining.
Heterogeneity is inevitable.
Basically, current algorithms assume the homogeneity. Thus if we naively apply them to heterogeneous system, its performance is far below expectation. We need some new methodologies to handle heterogeneity. In this paper, we propose the new dynamic load balancing methods for association rule mining, which works under heterogeneous system. Two strategies, called candidate migration and transaction migration are proposed.