A novel algorithm applied to classify unbalanced data
Applied Soft Computing
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The performance of parallel transaction processing systems can be degraded significantly due to data skew, a phenomenon of unbalanced data distribution over nodes of a system. Rebalancing the data load of the system with data skew by redistributing its data has been known to be an effective approach to coping with data skew. Unfortunately, for most of the existing approaches, the data being redistributed is unavailable (off line). Numerous applications such as that for reservations, finance, process control, hospitals, police, and armed forces, however, cannot afford off-line data for any significant amount of time. These applications call for the ability of balancing data load on line. In this paper, a new on-line data redistribution approach is proposed. A prototype of the approach has been implemented, and experiments have been conducted. Experiment results confirm the substantial performance gains of the approach.