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Sensors (Basel)


Title:A Data-Gathering Scheme with Joint Routing and Compressive Sensing Based on Modified Diffusion Wavelets in Wireless Sensor Networks
Author(s):Gu X; Zhou X; Sun Y;
Address:"College of Computer and Information, Hohai University, Naijing 210098, China. xpgu2010@hyit.edu.cn. Faculty of Electronic Information Engineering, Huaiyin Institute of Technology, Huai'an 223003, China. xpgu2010@hyit.edu.cn. College of Computer and Information, Hohai University, Naijing 210098, China. zhouxf@hhu.edu.cn. School of Information and Control Engineering, China University of Mining and Technology, Xuzhou 221116, China. yjsun@cumt.edu.cn"
Journal Title:Sensors (Basel)
Year:2018
Volume:20180228
Issue:3
Page Number: -
DOI: 10.3390/s18030724
ISSN/ISBN:1424-8220 (Electronic) 1424-8220 (Linking)
Abstract:"Compressive sensing (CS)-based data gathering is a promising method to reduce energy consumption in wireless sensor networks (WSNs). Traditional CS-based data-gathering approaches require a large number of sensor nodes to participate in each CS measurement task, resulting in high energy consumption, and do not guarantee load balance. In this paper, we propose a sparser analysis that depends on modified diffusion wavelets, which exploit sensor readings' spatial correlation in WSNs. In particular, a novel data-gathering scheme with joint routing and CS is presented. A modified ant colony algorithm is adopted, where next hop node selection takes a node's residual energy and path length into consideration simultaneously. Moreover, in order to speed up the coverage rate and avoid the local optimal of the algorithm, an improved pheromone impact factor is put forward. More importantly, theoretical proof is given that the equivalent sensing matrix generated can satisfy the restricted isometric property (RIP). The simulation results demonstrate that the modified diffusion wavelets' sparsity affects the sensor signal and has better reconstruction performance than DFT. Furthermore, our data gathering with joint routing and CS can dramatically reduce the energy consumption of WSNs, balance the load, and prolong the network lifetime in comparison to state-of-the-art CS-based methods"
Keywords:ant colony algorithm compressive sensing data gathering diffusion wavelets wireless sensor networks (WSNs);
Notes:"PubMed-not-MEDLINEGu, Xiangping Zhou, Xiaofeng Sun, Yanjing eng Switzerland 2018/03/03 Sensors (Basel). 2018 Feb 28; 18(3):724. doi: 10.3390/s18030724"

 
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