基于压缩感知的WSN大数据采集新方法

De-gan Zhang, Xiao-hua Liu, Yu-ya Cui, Hong-tao Peng
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引用次数: 0

摘要

针对无线传感器网络的聚类结构,提出了一种基于压缩感知的大数据采集方法。收集过程如下:在集群中,汇聚节点根据网络分布设置相应的种子向量,然后发送到每个簇头。簇头根据接收到的种子向量生成自己的随机间距稀疏矩阵,通过压缩感知技术采集数据;在集群之间,集群沿着我们之前建立的多跳路由树将测量值转发给汇聚节点。性能分析和对比结果表明,该方法无论在集群内还是集群间都优于其他方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
New Big Data Collecting Method Based on Compressive Sensing in WSN
Considered the wireless sensor network clustering structure, a new big data collecting method based on compressive sensing is proposed. The collection process is as follows: 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 sink node along multi-hop routing tree which we built before. Performance analyzing and comparison of results show that this method is superior to other methods regardless of in a cluster or inter-cluster.
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