北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2018, Vol. 41 ›› Issue (2): 119-124.doi: 10.13190/j.jbupt.2017-190

• 研究报告 • 上一篇    

使用改进灰色模型的WSN数据压缩方法

段利国1, 朱丽1, 李晓伟2, 李爱萍1   

  1. 1. 太原理工大学 信息与计算机学院, 山西 晋中 030600;
    2. 北方自动控制技术研究所, 太原 030006
  • 收稿日期:2017-11-18 出版日期:2018-04-28 发布日期:2018-03-17
  • 作者简介:段利国(1970-),男,副教授,硕士生导师,E-mail:463035793@qq.com.
  • 基金资助:
    国家自然科学基金项目(61472271)

Data Compression Method of WSN Used Improved Grey Model

DUAN Li-guo1, ZHU Li1, LI Xiao-wei2, LI Ai-ping1   

  1. 1. College of Information and Computer, Taiyuan University of Technology, Shanxi Jinzhong 030600, China;
    2. North Automatic Control Technology Institute, Taiyuan 030006, China
  • Received:2017-11-18 Online:2018-04-28 Published:2018-03-17

摘要: 针对数据压缩方法计算复杂度高、压缩效率和数据恢复准确率较低的情况,提出一种基于簇头-基站分离式结构的无线传感器网络(WSN)数据压缩方法.该方法在WSN单层分簇结构的基础上,首先要求感知节点等时间间隔采集数据,并分段发送;然后采用原有空间相关性数据压缩方法对簇头节点接收的数据进行空间噪声及冗余的消除;最后在基站采用改进的灰色模型进行数据恢复.另外,通过实验分析不同段长及压缩率情况下,灰色模型、灰色马尔可夫链模型以及改进的灰色模型对数据的恢复效果,给出算法的最优模型和段长.仿真结果表明,提出的方法较已有线性类WSN数据压缩方法可显著提高压缩精度和效率.

关键词: 无线传感器网络, 空间相关性, 数据压缩, 改进灰色模型

Abstract: In view of high computational complexity, low compression efficiency and data recovery rate of current data compression methods of wireless sensor network, a wireless sensor networks (WSN) data compression method based on a cluster head base station separation structure is proposed. Based on the monolayer cluster structure of WSN, the method requests the terminal sensor node to collect data at equal intervals and transmit data in segments at first. Then the spatial correlation data compression method is performed to eliminate the space noise and space redundancy of data in cluster head node. Finally, the improved grey model is adopted for data recovery at the base station. In addition, the optimal model and segment length of the algorithm are given, through the experimental analysis of the data recovery effect of the improved grey model, the grey model and the grey Markov chain model. Experimental results show that, compared with the existing linear WSN data compression methods, the proposed method significantly improves the WSN compression accuracy and efficiency.

Key words: wireless sensor networks, spatial correlation, data compression, improved grey model

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