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首页> 外文期刊>Pervasive and Mobile Computing >An energy-efficient data gathering method based on compressive sensing for pervasive sensor networks
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An energy-efficient data gathering method based on compressive sensing for pervasive sensor networks

机译:基于普及传感器网络压缩感测的节能数据收集方法

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摘要

AbstractThis paper proposes an energy-efficient data gathering method called CN-MSTP (Combining Minimum Spanning Tree with Interest Nodes) for pervasive wireless sensor networks, basing on Compressive sensing (CS) and data aggregation. The proposed CN-MSTP protocol selects different nodes at random as projection nodes, and sets each projection node as a root to construct a minimum spanning tree by combining with interest nodes. Projection node aggregates sensor reading from sensor nodes using compressive sensing. We extend our method by letting the sink node participate in the process of building a minimum tree and introduce eCN-MSTP. We compare our methods with the other methods. Simulation results indicate that our two methods outperform the other methods in overall energy consumption saving and load balance and hence prolong the lifetime of the network.]]>
机译:<![cdata [ Abstract 本文提出了一种称为CN-MSTP(与兴趣节点的最小生成树)的节能数据收集方法,用于普及无线传感器网络,基于基础关于压缩传感(CS)和数据聚合。所提出的CN-MSTP协议随机选择不同的节点作为投影节点,并将每个投影节点设置为根,以通过与兴趣节点组合来构造最小的生成树。投影节点使用压缩感测从传感器节点聚合传感器读取。我们通过让水槽节点参与构建最小树并引入ECN-MSTP的过程来扩展我们的方法。我们将我们的方法与其他方法进行比较。仿真结果表明,我们的两种方法优于整体能耗节省和负载平衡的其他方法,因此延长了网络的寿命。 ]]>

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