Specifically, we improve the advantage of data mining parallelization by considering the time overlap: (a) across computing nodes; and (b) between data transfer delay and computation time in each computing node. While unequal loads may be apportioned to the parallel computing nodes, our algorithm can still make sure that outputs are produced at the same time without any single slow node acting as a bottleneck.