DCT-Based Adaptive Data Compression in Wireless Sensor Networks

Siguang Chen, Jincheng Liu, Meng Wu, Zhixin Sun

Abstract: Wireless sensor networks (WSNs) provide a promising approach to monitor the physical environments, to prolong the network lifetime by exploiting the mutual correlation of sensor readings has become a research focus. In this paper, we propose a hierarchical network framework and adaptive threshold compression scheme to reduce the amount of information transmissions and alleviate the network congestion by exploring the spatial correlation among signals. The adaptive spatial compression scheme can obtain higher reconstruction precision by selectively discarding the less significant elements. Meanwhile, the compression ratio varies with the correlation among signals and adaptive threshold, so our scheme is adaptive to various deployed environments. Finally, the simulation results confirm that the proposed scheme achieves higher reconstruction precision and compression gain as compared with other spatial compression scheme.