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A kind of effective data aggregating method based on compressive sensing for wireless sensor network

机译:一种基于无线传感器网络压缩感测的一种有效的数据汇总方法

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Wireless sensor network (WSN) in the Internet of Things consists of a large number of nodes. The proposal of compressive sensing technology provides a novel way for data aggregation in WSN. Based on the clustering structure of WSN, a kind of effective data aggregating method based on compressive sensing is proposed in this paper. The aggregating process is divided into two parts: in the cluster, the sink node sets the corresponding seed vector based on the distribution of network and then sends it to each cluster head. Cluster head can generate corresponding own random spacing sparse matrix based on its received seed vector and collect data through compressive sensing technology. Among clusters, clusters forward measurement values to the sink node along multi-hop routing tree. Performance analysis and comparison with the relative methods show that our method is effective and superior to other methods regardless of intra-cluster or inter-cluster on the total energy consumption of network.
机译:Internet Internet Internet的无线传感器网络(WSN)包括大量节点。压缩传感技术的提议为WSN中的数据聚集提供了一种新的方法。基于WSN的聚类结构,本文提出了一种基于压缩感测的有效数据聚集方法。聚合过程分为两部分:在群集中,汇聚节点基于网络的分布设置相应的种子矢量,然后将其发送到每个簇头。簇头可以基于其接收的种子矢量产生相应的自动间隔稀疏矩阵,并通过压缩传感技术收集数据。在集群中,串联沿多跳路由树向汇聚节点向前的测量值。性能分析和与相对方法的比较表明,无论网络总能耗,我们的方法都是有效且优于其他方法,无论网络的总能量消耗如何。

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