Data Compression optimization Strategy based on Piecewise Fitting and Matrix Completion for WSNs
Shuang Zhai, Zhihong Qian, Xin Wang, Xue Wang · 2019
The data transmitted in Wireless Sensor Networks (WSNs) have the characteristics of high redundancy and low rank. How to reduce the compression rate and computing burden of cluster-head node and improve the data reconstruction accuracy of sink node is a research hotspot in the field of data acquisition and processing technology in WSNs. For clust-head and sink node in WSNs, data compression based on piecewise fitting and data reconstruction strategy of sink node based on matrix completion were proposed respectively. Clust-head and sink node implement their respective compression strategies: Cluster head classifies and compresses the perceived data to reduce the data correlation; the sink node receives the compressed data from the cluster-heads, and then recover the data by matrix completion. Simulation results show that the proposed algorithms effectively reduce the compression ratio and improve the accuracy of data reconstruction.