Fused-Schedule-Buffer Based Data Preparation Mechanism for Generating Target Association Rules

Target Association Rules (TARs) is a recent proposed behavioral patterns that captures the temporal correlations among a set of monitored objects. However, preparing the data needed to generate these rules is a costly process. In this paper, we propose a new energy-efficient data preparation mechanism, named Fused-Schedule-Buffer based technique, to prepare the data needed for generating TARs. Several experiments have been conducted to compare the performance of the new proposed mechanism with the other proposed techniques. Results have shown the outperforming of the Fused-Schedule-Buffer technique in terms of energy consumption.

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