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| 传感器网络中基于环模型的小波数据压缩算法 |
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周四望1, 林亚平1,2, 张建明1, 欧阳竞成1, 卢新国1
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1.湖南大学,计算机与通信学院,湖南,长沙,410082;2.湖南大学,软件学院,湖南,长沙,410082
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| 摘要: |
| 无线传感器网络有限的资源,如能量、通信带宽等,难以适应网络中大量数据的传输,需要在网络内部对原始监测数据进行压缩或聚合处理.设计了一个适合小波变换的环模型.针对任意支撑长度的小波函数,给出了一种基于环模型的分布式时-空小波数据压缩算法.该算法将传感器网络中的数据抽象为一个矩阵,将时间相关性与空间相关性映射为该矩阵的小波列变换与行变换,以同时挖掘传感器网络中数据的时间和空间相关性.从能量消耗和网络延时两方面定性地分析了算法的性能.理论分析和实验结果表明,该算法能够有效地去除传感数据中存在的时间和空间相关性, |
| 关键词: 无线传感器网络 环模型 小波变换 压缩 |
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| 基金项目:Supported by the National High-Tech Research and Development Plan of China under Grant No.2006AA01Z227(国家高技术研究发展计划(863)),the Natural Science Foundation of Hu'nan Province of China under Grant No.06JJ20049(湖南省自然科学基金) |
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| A Wavelet Data Compression Algorithm Using Ring Topology for Wireless Sensor Networks |
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ZHOU Si-Wang,LIN Ya-Ping,ZHANG Jian-Ming,OUYANG Jing-Cheng,LU Xin-Guo
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| Abstract: |
| Wireless sensor networks usually have limited energy and transmission capacity, and they can’t match the transmission of a large number of data. So, it is necessary to perform in-network compression or aggregation of the raw data sampled by sensors. By designing a ring topology, this paper proposes an algorithm for wavelet based spatio-temporal data compression in wireless sensor networks. The algorithm is capable of supporting a broad scope of wavelets that can simultaneously explore the spatial and temporal correlations among the sensory data. In this algorithm, the data in sensor networks are abstracted as a matrix, and the temporal and spatial correlation is then captured by the column and row wavelet transform respectively. The performance of the algorithm is qualitatively analyzed from the viewpoints of energy and delay. Theoretically and experimentally, it is concluded that the proposed algorithm can effectively explore the spatial and temporal correlation in the sensory data and provide a significant reduction in energy consumption and delay. |
| Key words: wireless sensor network ring topology wavelet transform compression |
