北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2016, Vol. 39 ›› Issue (2): 15-19.doi: 10.13190/j.jbupt.2016.02.003

• 论文 • 上一篇    下一篇

面向数据压缩的无线多媒体传感器网络节点选择方法

肖甫1,2, 杨谢琨1, 孙力娟1,2, 王汝传1,2, 唐晓璇3   

  1. 1. 南京邮电大学 计算机学院, 南京 210003;
    2. 江苏省无线传感网高技术研究重点实验室, 南京 210003;
    3. 北京邮电大学 网络与交换技术国家重点实验室, 北京 100876
  • 收稿日期:2015-03-15 出版日期:2016-04-28 发布日期:2016-04-28
  • 作者简介:肖甫(1980-),男,教授,博士生导师,E-mail:Xiaof@njupt.edu.cn.
  • 基金资助:

    国家自然科学基金项目(61373137,61373017,61373139);江苏省高校自然科学重大项目(14KJA520002);江苏省六大人才高峰项目(2013-DZXX-014);国家高技术研究发展计划(863计划)项目(2011AA05A116)

Node Selection Approach for Data Compression in Wireless Multimedia Sensor Networks

XIAO Fu1,2, YANG Xie-kun1, SUN Li-juan1,2, WANG Ru-chuan1,2, TANG Xiao-xuan3   

  1. 1. College of Computer, Nanjing University of Posts and Telecommunications, Nanjing 210003, China;
    2. Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks, Nanjing 210003, China;
    3. State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China
  • Received:2015-03-15 Online:2016-04-28 Published:2016-04-28

摘要:

针对多媒体传感网采集图像信息的空间冗余问题,提出了一种面向数据压缩的无线多媒体传感器网络节点的选择方法.该方法从节点3维感知模型出发,设计空间相关模型以描述感知图像数据之间的相关性,在此基础上,提出基于相关性的节点选择方法,减少了采集数据的空间冗余.仿真实验结果验证了新方案的有效性.

关键词: 无线多媒体传感器网络, 相关性模型, 节点选择, 空间冗余

Abstract:

Multimedia sensor network is an advanced form of sensor networks. It has multimedia information perception, processing and transmission capacity. For the problem of great redundancy and correlation in the collection data, a node selection approach for data compression was designed. By using the correlation model based on three-dimensional perception, it describes the relevant characteristics between the observed images data. Then the camera node selection algorithms was proposed based on correlation coefficients to reduce the spatial redundancy of sensing data. A set of comparisons are performed to evaluate the effective of our algorithms.

Key words: wireless multimedia sensor networks, correlation model, node selection, spatial redundancy

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