An Adaptive Compression Algorithm for Wireless Sensor Network Based on Piecewise Linear Regression
The wireless sensor network (WSN) has limited bandwidth, low power consumption, and may have redundantly collected data. The effective compression of data to reduce the energy consumption in transmission is of great importance. To this end, we proposed a new data-compression algorithm for WSN. The key idea of the algorithm is based on an adaptive threshold and piecewise linear fitting. The adaptive threshold is automatically adjusted by error after the fitting model was applied to the rationality of the adjusted model; subsequently linear fitting is used to determine the reasonable range of subsection based on the detection of continuous unfitting points. From the simulation results, the algorithm is realized in low time complex but with a good data compression effect, and then has a potential practicability.
This work was supported in part by the National Natural Science Foundation of China (no. 61401453), the STS Key Health Program of Chinese Academy of Sciences (no. KFJEW-STS-097 and KFJ-EW-STS-095), the External Cooperation Program of the Chinese Academy of Sciences (GJHZ1212), the Guangdong Innovation Research Team Fund for Low-Cost Healthcare Technologies in China, and the Key Lab for Health Informatics of Chinese Academy of Sciences, the Enhancing Program of Key Laboratories of Shenzhen City (no. ZDSY20120617113021359).
- 4.X. Y. Liu, Y. Z. Wang, X. C. Yang. Study on Compression Technique for Streaming Data in Wireless Sensor Networks[J]. Computer Science, 2007, 34(2): 141–143.Google Scholar
- 6.E. Soroush, K. Wu, J. Pei. Fast and quality-guaranteed data streaming in resource-constrained sensor networks. In: Proc. of the MobiHoc. New York: ACM Press, 2008. 391–400.Google Scholar
- 8.J. L. Wang, S. W. Zhou, H. Tang. Regression-based Wireless Sensor Network Data Compression Method. Computer Engineering, 2011, 37(23): 96–98.Google Scholar