Voronoi Tessellation Based Haar Wavelet Data Compression for Sensor Networks

We propose a distributed wavelet-based algorithm which can transform irregularly sample data using Haar wavelet-based compression solutions in this paper. We consider the characteristics and location information of nodes in sensor networks, a new distributed data aggregation mode based on "area" is used firstly. On the basis of these new models, a novel wavelet-based irregularly sample data compression and data transform model DDCM is proposed for sensor networks. Theoretical analyses and simulation results show that, the above new methods have the good ability of approximation, and can compress the data efficiently and can reduce the amount of data greatly. So, it can prolong the lifetime of the whole network to a greater degree