A Prediction Based Data Aggregation Scheme in Wireless Sensor Networks

It is very important to minimize the amount of data transmission in wireless sensor networks so that the average sensor lifetime and the overall bandwidth utilization can be improved. In this paper, we propose a prediction based data aggregation scheme which takes advantage of temporal data correlation among sensors to monitor continuously changed environmental conditions. A seasonal time series model is built up to predict the sensed values of ordinary sensors according to the collected historical data. The experiment results show that our proposed scheme can provide considerable aggregation ratio while maintaining a low prediction error rate.