Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Energy efficiency prediction method of WSN data lossy compression algorithm based on linear fitting

A compression algorithm and linear fitting technology, applied in forecasting, data processing applications, calculations, etc., can solve problems such as inappropriate promotion, time-consuming and labor-intensive

Inactive Publication Date: 2017-01-04
CENT SOUTH UNIV
View PDF2 Cites 5 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This method is time-consuming and laborious, and should not be promoted

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Energy efficiency prediction method of WSN data lossy compression algorithm based on linear fitting
  • Energy efficiency prediction method of WSN data lossy compression algorithm based on linear fitting
  • Energy efficiency prediction method of WSN data lossy compression algorithm based on linear fitting

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0090] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0091] The invention discloses an energy efficiency prediction method based on a linear fitting WSN data lossy compression algorithm, comprising the following steps:

[0092] Step 1) Select sensor nodes and WSN data lossy compression algorithm based on linear fitting

[0093] The compression algorithm selects the PMC-MR algorithm in the wireless sensor network data lossy compression algorithm based on linear fitting, and the compression object selects sample data that obeys Gaussian distribution. The microcontroller MCU of the sensor node is MSP430F2611, running at 3.0V, 512μA , under 1MHz; the wireless transmission module adopts CC2420, runs under 3.0V, 17.4mA, carries out data transmission with the baud rate of 150kpbs, is example with above-mentioned object and working parameter, the implementation application of the present invent...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention provides an energy efficiency prediction method of a WSN data lossy compression algorithm based on linear fitting. The method includes calculating the hardware coefficient k according to the hardware parameters of a sensor node; determining the relation between the compression ratio RC of the specific algorithm and the error tolerance Epsilon of the data compression by means of the polynomial fitting prediction method, and obtaining the predicted value of Rc according to the value of the given error tolerance Epsilon; predicting the relation between the software coefficient s and RC according to the algorithm code structure and determining the software coefficient s of the algorithm; and substituting the k value and the predicted values of s and Rc into an energy efficiency computational formula eta E=(Rc-s / k)*100% and obtaining the energy efficiency predicted value of the specific algorithm. The prediction method is only related to the compression coefficient and the compression ratio and the error tolerance under the condition that the compression algorithm has no errors, can predict the algorithm energy efficiency under the given error tolerance online and can correct the compression ratio prediction formula. The prediction method is simple in calculation and low in energy consumption, and provides the basis for selecting the energy efficient compression algorithm online for the sensor node in WSN.

Description

technical field [0001] The technology of the present invention relates to an online prediction method of energy efficiency of a data compression algorithm, which is suitable for a lossy data compression algorithm based on linear fitting in a wireless sensor network, and is mainly used for online selection of a compression algorithm according to the compression accuracy requirements, so as to Save electricity more efficiently. Background technique [0002] With the rapid development of system on chip (SoC), micro electro mechanical system (MEMS), embedded system low power consumption technology and sensor technology, as a comprehensive intelligent information processing platform, wireless sensor network (Wireless Sensor Networks, WSN) has been widely accepted. It has broad application prospects and is one of the most active hotspots in the field of computer information research, as well as one of the major technologies that will change future life. [0003] WSN uses sensor n...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04
CPCG06Q10/04
Inventor 刘少强刘延芳樊晓平徐文闫晓燕
Owner CENT SOUTH UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com