压缩域下的数据融合在传感器网络中的应用

针对无线传感器网络数据融合中传输数据量高、能耗大的问题,研究基于压缩感知的数据融合方案,并提出在压缩域直接数据融合的算法.该算法通过配置传感器网络以生成多个层次类型不同的簇结构,提高数据在不同层次的压缩率,减少了网络中的传输数据量和传输能耗.压缩后的数据在网络中传输,并在各层簇头实现压缩域下的数据融合.通过仿真实验和标准数据库SensorScope真实气象数据测试,该算法在保证准确重建的基础上,在减少传输数据量方面都有较大优势,适用于较大规模的无线传感器网络.

Data aggregation based on compressed domain in wireless sensor network

A data fusion scheme based on compressed sensing is studied and a data fusion algorithm performed directly in the compressed domain is proposed to solve the problem of excessively high amount of data transmission and excessive energy consumption in wireless sensor networks.By configuring the sensor networks to generate cluster structures with different hierarchical types and improving the compression ratio of data at different layers,the algorithm reduces the amount of data transmission and energy consumption of the networks.The compressed data is transmitted in the network,and the data fusion in the compressed domain is performed in the cluster heads of each layer.The simulation experiment and the test results of real data from SensorScop database show that the proposed algorithm has advantages in reducing the amount of data transmission on the base of reconstruction and is suitable for large scale wireless sensor networks.