A sensor node lossless compression algorithm for non-slowly varying data based on DMD transform

Abstract

Efficient utilization of energy is a core area of research in wireless sensor networks. Data compression methods to reduce the number of bits to be transmitted by the communication module will significantly reduce the energy requirement and increase the lifetime of the sensor node. Based on the lifting scheme 2-point discrete cosine transform (DCT), this paper proposed a new reversible recursive algorithm named Difference-Median-Difference (DMD) transform for lossless data compression in sensor node. The DMD transform can significantly reduce the spatio-temporal correlations among sensor data and can smoothly run in resource limited sensor nodes. Through an entropy encoder, the results of DMD transform can be compressed more compactly based on their statistical characteristics to achieve compression. Compared with the typical lossless algorithms, the proposed algorithm indicated better compression ratios than others for non-slowly-varying data, despite a less computational effort.