An enhanced data reduction mechanism to gather data for mining sensor association rules

Sensor association rules have been found to be very useful for improving the quality of service, energy conservation, resource management, etc. in wireless sensor networks (WSN). To mine sensor association rules, behavioral data, which describes the sensor activities, are required to be sent to the central node (sink node) by the sensors. However, it is not feasible for the sensors to send the whole behavioral data to the sink because of the limited resources such as power, processing capacity, storage, etc. available to the sensors. So, efficient data gathering mechanisms are required for sensor association rule mining. One recent and efficient data gathering mechanism for sensor networks has been proposed by Azzedine et. al, which exploits redundancy between sensor activities and uses a data gathering tree called MNDGT (Minimum Node Data Gathering Tree). In this paper, we have tried to enhance the algorithm proposed by Azzedine et. al by removing more redundancy between sensor activities. Simulated experimental results have shown that the enhanced version has reduced the amount of data to be sent to the sink to a great extent.