Data Compression Algorithm Based on Sequence Correlation for WSN
Shuang Zhai, Zhihong Qian, Liu Xiaohui, Sun Da-yang · JOURNAL OF ELECTRONICS INFORMATION TECHNOLOGY · 2016
The data has correlations and redundancy in Wireless Sensor Network (WSN). How to reduce effectively the amount of communication data and extend the network life cycle is one of researching hot points. The Two-Step data Compression algorithm based on Sequence Correlation (TSC-SC) for WSN is proposed in this paper. The cluster head and the nodes in clusters perform different compression algorithms for themselves. In order to eliminate the spatial correlation of data and reduce the calculated amount, the cluster head nodes perform the grouping algorithm firstly, then the nodes in clusters perform the classifing compression to eliminate correlation for multi-attribute data, and pass the compression parameters to the cluster head; the cluster head perform the classifing compression again after decompressing the parameters. So the data-redundancy and communication energy consumption is further reduced. A new evaluation model named Network Compression Energy Ratio (NCER) based on energy discrimination is also proposed. The evaluation model realizes comprehensive evaluation of compression algorithms by considering both the basic requirements of compression and calculated energy consumption in the nodes. Simulation results show that TSC-SC algorithm can reduce the compression ratio and compression error effectively; the amount of communication data and energy consumption can achieve a satisfactory level in the network. The algorithm can be estimated directly using NCER.