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Pretreatment method for wavelet data compression in sensor network

A sensor network and data compression technology, applied in the direction of network traffic/resource management, network topology, transmission system, etc., can solve the problem of reducing the monitoring performance of sensor networks

Active Publication Date: 2015-01-21
LUOYANG INST OF SCI & TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The transmission of a large amount of redundant data will greatly reduce the monitoring performance of the sensor network

Method used

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  • Pretreatment method for wavelet data compression in sensor network
  • Pretreatment method for wavelet data compression in sensor network
  • Pretreatment method for wavelet data compression in sensor network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0091] Example 1, set the error requirement of the reconstructed data as MSE, and change it from 10 to 100, and calculate the average data compression rate, the simulation results are as follows image 3 As shown, specifically, under the same reconstruction data error requirements, the data compression rate obtained by DSPS using db1, db2, coif1 and bior2.2 wavelets of the present invention is lower than the data compression rate obtained by CWA using these wavelets, It has better data compression effect. In addition, among db1, db2, coif1 and bior2.2 wavelets, whether it is the present invention or CWA, in this experimental environment, db1 wavelet is better for data compression.

Embodiment 2

[0092] Embodiment 2, the data compression rate is changed from 0.1 to 0.9, and the network average MSE of the two schemes under different wavelet data processing are respectively counted, and the simulation results are as follows Figure 4 As shown, specifically, under db1, db2, coif1 and bior2.2 wavelets, when the data compression rate is fixed at 0.1, the MSE obtained by DSPS of the present invention is much smaller than the MSE obtained by CWA; and with the increase of data compression rate Although the MSE gap between the present invention and CWA gradually decreases, the data reconstruction accuracy of the present invention is still better than that of CWA.

Embodiment 3

[0093] Embodiment 3, the data compression rate is changed from 0.1 to 0.9, and the average energy consumption of the network nodes of the two schemes under different wavelet data processing are respectively counted, and the simulation results are as follows Figure 5 As shown, specifically, under the same data compression rate, no matter what kind of wavelet is used, the energy consumption of DSPS in the present invention is more than that of CWA, but the increase in energy consumption is very small, and it can obtain more accurate than CWA The data( Figure 4 shown). This is because, under the same data compression rate, the present invention has the same data transmission energy consumption as CWA, but relative to CWA, the present invention has two aspects of additional energy consumption: (1) the energy consumption when updating the mean value of cluster member nodes energy and (2) the energy consumption when the node sequence index of the cluster head node is updated. Th...

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Abstract

The invention discloses a pretreatment method for wavelet data compression in sensor network. The pretreatment method comprises a cluster member node behavior and a cluster head node behavior. The cluster member node behavior mainly comprises the procedures that a sample average and a sample standard deviation of K perception data serve as approximate data features of environment of a cluster member node; the sample average change degree is utilized for balancing the changing degree of the environment; a cluster head node is informed of the corresponding sample average; the cluster head node behavior mainly comprises the procedures that a sample average of the cluster member node is utilized, and the cluster head node builds and maintains a sequential index of the cluster member node; the cluster head node obtains data of all cluster member nodes and generates a data vector according to the sequential index; discrete wavelet transform is carried out on the data, and an obtained approximation coefficient and part of coefficients are sent to a base station; invert wavelet transform is utilized, and the base station completes reconstitution of the perception data of the nodes in the cluster according to the obtained coefficients and the sequential index of the corresponding cluster member node.

Description

technical field [0001] The invention relates to the field of data processing in the field of wireless sensor networks in the field of computer network technology, in particular to a preprocessing method for wavelet data compression in sensor networks. Background technique [0002] In order to obtain sufficient monitoring of the environment, the distribution of sensor network nodes is usually relatively dense, and a large amount of raw sensing data with large redundancy is generated in the network. The transmission of a large amount of redundant data will greatly reduce the monitoring performance of the sensor network. Therefore, the original data must be processed in the network to reduce the redundancy between data and reduce the amount of data transmission in the network, so as to prolong the working time of the sensor network. [0003] Compared with Fourier analysis, wavelet is a new time-frequency analysis tool, which can simultaneously characterize the time-domain and ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04W84/18H04L29/08
CPCH04W28/06H04W84/18H04L67/5651Y02D30/70
Inventor 聂雅琳秦玉洁
Owner LUOYANG INST OF SCI & TECH
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