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无线传感器网络中数据汇聚方案的研究
引用本文:周林,陈扬扬. 无线传感器网络中数据汇聚方案的研究[J]. 电视技术, 2012, 36(13): 71-73
作者姓名:周林  陈扬扬
作者单位:重庆邮电大学,重庆邮电大学
基金项目:基于物联网技术的呼吸、脉博异变及跌落的实时监测与报警的关键技术研究
摘    要:针对分簇网络拓扑结构中簇头节点能量消耗过快,综合考虑了节点的密集程度和剩余能量,采用节点自适应的簇头选择算法,选择部署越集中和剩余能量越大的节点作为簇头节点。同时节点引入了新鲜性信息熵模型,通过比较前后两次接收到的数据的差别程度,设置一个参考阈值来判断是否转发数据。这种数据汇聚算法有效地降低了数据的冗余,减少了能量消耗,增加了带宽利用率,延长了网络的生存期。

关 键 词:无线传感器网络  数据汇聚  选择簇头  信息熵
收稿时间:2012-03-31
修稿时间:2012-04-26

Research on Data aggregation scheme of wireless sensor networks
zhoulin and chenyangyang. Research on Data aggregation scheme of wireless sensor networks[J]. Ideo Engineering, 2012, 36(13): 71-73
Authors:zhoulin and chenyangyang
Affiliation:Department of Communication and Information Engineering,Chongqing University of Posts and Telecommunications,Department of Communication and Information Engineering,Chongqing University of Posts and Telecommunications
Abstract:According to the cluster network topology, the energy of cluster head node consume too fast. considering the intensity and the residual energy of nodes, We use node adaptive cluster head selection algorithm to select the cluster head node which is deployed more concentrated and has more residual energy. This paper introduces a fresh information entropy model, comparing the two received data between the last time and this time, we set a reference threshold value to determine whether to forward data. This data aggregation algorithm can reduce data redundancy, reduce energy consumption; increase bandwidth utilization and extend the network lifetime.
Keywords:wireless sensor networks   data aggregation   cluster head   information entropy  
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