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无线传感器网络中基于区域相关性的自组织成簇算法 被引量：3

Self-organized clustering algorithm based on regional relevance in wireless sensor network
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摘要 无线传感器网络资源有限,信息量大,通常采用分簇压缩减少传输量。针对传感器网络中的小波压缩,提出了一种基于相关区域自组织的成簇算法。该算法利用实际区域数据的相关性进行分簇,在簇头进行小波数据压缩的同时进行相关性检测,动态调整簇结构,保证簇内节点的相关性较好;同时在Sink分析簇间节点数据相关性,形成相关性好的大规模簇,进一步提高较长时间内的压缩效率。理论分析和实验仿真表明,该算法能尽可能地利用节点数据的时间和空间相关性去除冗余数据,提高小波数据压缩效率,降低了网络的能耗。 In view of limited resources and amounts of data in Wireless Sensor Network（WSN）,clustering compressions are always employed to reduce transmission packets.Based on the regional relevance,a self-organized clustering algorithm was proposed for the wavelet compression in sensor network.The algorithm used the correlation of actual regional data for clustering.Actually,during the wavelet data compression procedure,the data correlation was detected in the cluster head,so that to insure better correlation and adjust the clusters structure.Meanwhile,data dependence among the nodes was analyzed in Sink,to form large-scale clusters with better relevance,so that to improve the efficiency of wavelet compression in a long period.Theoretical and experimental results show that the proposed algorithm can eliminate the data redundancy by using temporal and spatial correlation as much as possible,improve the efficiency of wavelet data compression,and reduce network energy consumption.
作者 李玮 胡玉鹏
机构地区 湖南大学软件学院 湖南大学计算机与通信学院
出处 《计算机应用》 CSCD 北大核心 2010年第3期729-732,共4页 journal of Computer Applications
关键词 无线传感器网络 相关性 成簇 小波压缩 Wireless Sensor Network（WSN） correlation clustering wavelet compression
分类号 TP393 [自动化与计算机技术—计算机应用技术]
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参考文献12

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二级参考文献42

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共引文献658

同被引文献17

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引证文献3

二级引证文献8

计算机应用
2010年 第3期

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