计算机与现代化

• 网络与通信 • 上一篇    下一篇

无线传感器网络二代小波压缩的性能分析与研究

  

  1. 1.太原科技大学电子信息工程学院,山西太原030024;2.浙江大学宁波理工学院,浙江宁波315100
  • 收稿日期:2015-04-14 出版日期:2015-09-21 发布日期:2015-09-24
  • 作者简介:田洪周(1990-),男,山东泰安人,太原科技大学电子信息工程学院硕士研究生,研究方向:无线传感器网络; 通讯作者:应蓓华(1982-),女,浙江宁波人,浙江大学宁波理工学院, 博士,研究方向:无线传感器网络。
  • 基金资助:
     宁波市自然科学基金资助项目(2011A610185); 浙江省自然科学基金资助项目(LQ13F010005)

Analysis and Research on Performance of Compression Algorithm #br#  Based on Lifting Scheme Wavelet Transform in WSN

  1. 1. Institute of Electronic Information Engineering, Taiyuan University of Science and Technology, Taiyuan 030024, China;

     2. Ningbo Institute of Technology, Zhejiang University, Ningbo 315100, China
  • Received:2015-04-14 Online:2015-09-21 Published:2015-09-24

摘要:

能量的高效使用是无线传感器网络的首要设计目标,数据压缩能有效减少数据传输量及通信能耗,对延长网络寿命起着重要作用。针对无线传感器网络中的二代小波压缩算法对现有二代小
波的选择侧重计算复杂度而忽略实际节能效果的情况,本文以3种不同类型的数据为样本,对常用的各类二代小波进行分析、比较及验证,结果表明在相同误差容限下,2/6小波相比其它各类二代小波具
有更好的压缩效果及更大的能耗节省,更适用于无线传感器网络的应用。

关键词:  , 无线传感器网络, 数据压缩, 二代小波, 误差容限, 能耗

Abstract:

In the design of WSN (Wireless Sensor Network), how to use energy more effectively is the first design goal. Data compression can reduce the amount of data in
the process of transmission, which leads to not only improve the collection efficiency, but also reduce the energy consumption of wireless communication. It is very important
to prolong the life of the network. In the research of the data compression in WSN, compression algorithm based on lifting scheme wavelet transform focuses on computational
complexity and ignores the real energy saving effect when choosing wavelet transform. Aim at this situation, this paper, based on three different types of data as samples,
analyzed all kinds of lifting scheme wavelet transform which is used commonly for data compression and compared the performance of saving energy. The results of validation show
that under the same error tolerance, the 2/6 wavelet has better compression effect and more energy savings compared to the other kinds of wavelet. This makes it more suitable
for the application of data compression in WSN.

Key words:  WSN, data compression, wavelet transform based on lifting scheme, error tolerance, energy consumption