Efficient Data Suppression For Wireless Sensor Networks

Due to the critical resource restriction, wireless sensors often need to set a tradeoff between data transmission and accurate event detection. To address this issue, we propose a data reduction algorithm, SSS for WSN(Wireless Sensor Network). By exploiting the potential of the temporal and spatial correlations among sensory data, we make use of Singular Value Decomposition (SVD) for data suppression at sensor nodes. SSS is able to remove the unnecessary data transmission, so as to reduce the energy consumption and prolong the lifetime of the sensor network. Our experimental results show that SSS significantly reduce the amount of data transmission of sensor nodes, while retaining the capability of detecting the accidental events of the network.