Title: Farmland multi-parameter wireless sensor network data compression strategy

Authors: Feifei Li; Huaji Zhu; Huarui Wu

Addresses: Beijing Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China; National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China; Key Laboratories for Information Technology in Agriculture, Beijing 100097, China ' Beijing Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China; National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China; Key Laboratories for Information Technology in Agriculture, Beijing 100097, China ' Beijing Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China; National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China; Key Laboratories for Information Technology in Agriculture, Beijing 100097, China

Abstract: A certain correlation exists among farmland wireless sensor network (WSN) monitored parameter data. Analysing and utilising parameter correlation can improve data compression efficiency and reduce network communication power. A data compression algorithm for multi-parameter farmland WSN is proposed. Firstly, a compression matrix of each cluster is built up based on clustering analysis among parameters and internal correlation analysis between categories. Then the parameter sorting scheme is determined based on the structured matrix which had strong correlation among rows and columns. It conducted characteristic analysis of parameter sequences. Operators between parameters are built in order to enhance the correlation and reduce high-frequency component of the matrix. By doing these the information loss during compression process could be reduced, and realised the goals of elevating compression ratio and reducing compression errors. Compression test shows that the proposed algorithm can effectively reduce network data redundancy and energy consumption.

Keywords: WSN; wireless sensor network; data compression; correlation between parameters; wavelet transform.

DOI: 10.1504/IJAHUC.2018.095504

International Journal of Ad Hoc and Ubiquitous Computing, 2018 Vol.29 No.3, pp.221 - 231

Received: 02 Mar 2016
Accepted: 03 Oct 2016
Published online: 08 Oct 2018 *

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