An Energy-Efficient Data Collection Scheme Using Denoising Autoencoder in Wireless Sensor Networks

An Energy-Efficient Data Collection Scheme Using

Denoising Autoencoder in Wireless Sensor

Networks

Guorui Li;Sancheng Peng;Cong Wang;Jianwei Niu;Ying Yuan

【期刊名称】《清华大学学报（英文版）》 【年(卷),期】2024(024)001

【摘要】As one of the key operations in Wireless Sensor Networks (WSNs),the energy-efficient data collection schemes have been actively explored in the literature.However,the transform basis for sparsifing the sensed data is usually chosen empirically,and the transformed results are not always the sparsest.In this paper,we propose a Data Collection scheme based on Denoising Autoencoder (DCDA) to solve the above problem.In the data training phase,a Denoising AutoEncoder (DAE) is trained to compute the data measurement matrix and the data reconstruction matrix using the historical sensed data.Then,in the data collection phase,the sensed data of whole network are collected along a data collection tree.The data measurement matrix is utilized to compress the sensed data in each sensor node,and the data reconstruction matrix is utilized to reconstruct the original data in the sink.Finally,the

data

communication

performance

and

data

reconstruction performance of the proposed scheme are evaluated and compared with those of existing schemes using real-world sensed