WSNs Data Acquisition by Combining Hierarchical Routing Method and Compressive Sensing

Sensors

Zhiqiang Zou¹  Cunchen Hu¹  Fei Zhang¹  Hao Zhao¹ 

[1] Nanjing University of Posts and Telecommunications, Nanjing 210003, China; E-Mails:

关键词: compressive sensing;    wireless sensor networks;    sparse representation;    hierarchical routing method;    energy efficiency;   

DOI  :  10.3390/s140916766

来源: mdpi

【 摘 要 】

We address the problem of data acquisition in large distributed wireless sensor networks (WSNs). We propose a method for data acquisition using the hierarchical routing method and compressive sensing for WSNs. Only a few samples are needed to recover the original signal with high probability since sparse representation technology is exploited to capture the similarities and differences of the original signal. To collect samples effectively in WSNs, a framework for the use of the hierarchical routing method and compressive sensing is proposed, using a randomized rotation of cluster-heads to evenly distribute the energy load among the sensors in the network. Furthermore, L1-minimization and Bayesian compressed sensing are used to approximate the recovery of the original signal from the smaller number of samples with a lower signal reconstruction error. We also give an extensive validation regarding coherence, compression rate, and lifetime, based on an analysis of the theory and experiments in the environment with real world signals. The results show that our solution is effective in a large distributed network, especially for energy constrained WSNs.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland.