A distributed wavelet compression algorithm for wireless sensor networks

In this paper we proposed a novel distributed wavelet compression algorithm for reducing energy consumption in a wireless sensor network, where each of the sensors has limited power. This algorithm is characterized by a new lifting factorization which matches well with the transmission strategy employed in wireless sensor networks. We demonstrate that such schemes exploit the inherent correlations that exist between sensor readings, reduce algorithm computation complexity, and enhance data compression ratio. Then we discuss their impact on data quality. The simulation results showed that these approaches can achieve significant energy savings without sacrificing the quality of the data reconstruction.