关键词: 无线传感器网络, 混合压缩感知, 数据收集, 网络分簇, 负载均衡, 高效传输

Abstract: During the process of Wireless Sensor Network（WSN） data collection, reducing the number of data transmissions is vital for improving transmission efficiency and extending the lifetime of wireless sensor networks. Drawing on the experience of Compressive Sensing（CS）, a distributed hybrid compressive sensing data collection method for WSN is presented. Sensor nodes are divided uniformly into several clusters by using k-means++. Then distributed hybrid CS algorithm is implemented to gather data inside these clusters. After that, a backbone tree is built to gather data to the sink node. Simulation results show that, under the designated working condition （compressive ratio is equal to 10 and number of nodes is equal to 800）, compared with Shortest Path Tree Hybrid CS and optimal tree hybrid CS method, the proposed method can reduce 40% and 10% total number of transmissions correspondingly. Compared with the method without using CS, the proposed method can reduce over 70% of transmissions. Meanwhile, the standard deviation reduces from 14.07 and 14.37 to 11.85, and the length of confidence interval reduce from 322.66 and 131.75 to 39.12, which indicates that there are great improvements in aspects of robustness and load balance of the network.

Key words: wireless sensor network, hybrid compressive sensing, data collection, network clustering, load balancing, transmission efficient