A Multivariate Data Reduction Approach for Wireless Sensor Networks
Ibrahim Atoui, Abdallah Makhoul, Raphaël Couturier, Jacques Demerjian · 2021
Efficient data reduction methods are needed to minimize the power consumption in multivariate Wireless Sensor Network (WSN). In this paper, we proposed a distributed multivariate data reduction model for sensor nodes. It is based on reducing data matrices during two phases: in-network data aggregation and polynomial regression. To evaluate the performance of the proposed technique, experiments on real sensor data have been conducted. The obtained results show that our proposed technique outperforms the existing ones in terms of the size of data transmitted over the network and in terms of the energy consumption.