Research On Second Generation Wavelet Compression Algorithm For Wireless Sensor Networks

In the design of wireless sensor network(WSN), how to use energy more effectively is the first design goal. Data compression can reduce the amount of data in the process of transmission, which leads to not only improve the collection efficiency, but also reduce the energy consumption of wireless communication. It is very important to prolong the life of the network. During the development of data compression in WSN, on the premise of meeting the data accuracy, how to obtain energy savings by data compression is an important research content. Wavelet transform based on lifting scheme is not only simple,flexible and has a good effect in compressing streaming data. In this case, the analysis, design and verification on wavelet transform are proposed and realized in this paper to effectively reduce the energy consumption of the whole network.In the research of the data compression in WSN, compression algorithm based on lifting scheme wavelet transform focuses on computational complexity and ignores the real energy saving effect when choosing wavelet basis. Aim at this situation, this paper analyzes all kinds of lifting scheme wavelet transform which is used commonly for data compression and compares the performance of saving energy. The results of validation shows that under the same error tolerance, the 2/6 wavelet has better compression effect and more energy savings compared to the other kinds of wavelet. This makes it more suitable for the application of data compression in WSN.The low-frequency component after first-order data compression still exist redundancy. In order to further remove the redundancy and improve the effect of data compression, this paper chooses 2/6 wavelet as the research object and adopts second-order wavelet transform to compress the data. Meanwhile, based on three kinds of measured environmental data, the paper analyzes the relationships between compression ratio, error tolerance and energy consumption with different threshold settings in the twice wavelet transform. On the premise of meeting the preset error tolerance, corresponding to different types of raw data, the relationships on the threshold settings is proposed toobtain the optimal energy consumption.Finally, the compression algorithm is realized on the node platform.Through the temperature measuring, the feasibility and validity of compression are validated. The experimental results show that the compression algorithm can be well adapted to the characteristics of WSN, and has significant effect to reduce the energy consumption of nodes and the network.