Research On Compression Processing Method Of Agricultural WSN Based On Compression Sensing

Wireless sensor network(WSN)can effectively reduce the time of manual management and improve the efficiency of agricultural management.However,energy consuming about the network transmission of WSN is very huge,which can lead to premature death of note.The main purpose of this paper is to reduce the wireless sensor The data of the data is transmitted to reduce the energy consumption of the nodes,and a method of combining the correlation algorithm with the compression perception is proposed.In the farmland,the deployment of a large number of sensor nodes in the collection of environmental parameters inside,due to the sensor node energy is limited,a large number of data transmission,and traditional wireless communication sampling transmission,resulting in a large number of information redundancy information will shorten the life of the sensor node,so Reducing the amount of data transmission is the best way to reduce the energy consumption of the entire network and delay the service life of the network.At the same time,the compression perceptual algorithm is a data compression algorithm that has emerged in recent years.Because it is a simple compression,the complex algorithm is reconstructed,which is a new breakthrough in reducing the wireless transmission of WSN.For the time being,applying compression awareness to WSN is at the initial stage,but with the deepening of compression perception,its utility is more and more valuable.In this paper,the WSN data compression method based on compression perception is studied deeply,the main contents are as follows:1,access to the sensor node parameter data,the data correlation analysis,and data classification there are two: First,the single data analysis,the other is the multi-parameter data for correlation analysis.Then,the nodes with strong correlation are divided into the same group.After the grouping is finished,the average correlation is selected as the reference node,and the linear regression between the reference node and the non-reference node is calculated.2,describes the compression perception of the reconstruction algorithm.Reconstruction algorithm OMP,ROMP,focusing on these two algorithms,and to do experiments to compare.3,The simulation of correlation grouping algorithm and compression perception is carried out.First,the node data is clustered,for two cases to discuss: single parameter analysis,multi-parameter analysis.And then select the reference node in each group for compressed transport.And how to reconstruct the recovery rate in the case of different sparse rate,sparse base and observation matrix,so that the appropriate sparse rate,sparse base and observation matrix can be selected in the use of compression perception in WSN.