Distributed Compressed Sensing Algorithm for Cluster Architectures of WSNs

  • Nan Jiang College of Information Engineering, East China Jiaotong University Nanchang, 330013, JiangXi, P.R.China State Key Laboratory Breeding Base of Nuclear Resources and Environment, East China Institute of Technology, Nanchang, 330013, JiangXi, P.R. China *Corresponding author: jiangnan1018@gmail.com
  • Hui You College of Information Engineering, East China Jiaotong University Nanchang, 330013, JiangXi, P.R.China
  • Lingfeng Liu College of Information Engineering, East China Jiaotong University Nanchang, 330013, JiangXi, P.R.China
  • Feng Jiang School of Computer Science and technology, Harbin Institute of Technology Harbin, 15001, HeiLongJiang, P.R.China
  • Yueshun He College of Information Engineering, East China Institute of Technology Nanchang, 330013, JiangXi, P.R.China

Abstract

According to the traditional CS theory, each sensor node in the wireless sensor networks always is assumed to directly deliver relative information to sink node, which only considers the intra-signal correlation structure. In addition, these may lead to the loss of the node information and the overenergy consumption. To adjust the processing power and the energy limitation of the node, combined with the inter-signal correlation structure and the joint sparsity models - JSM1, this paper presents a new distributed compressed sensing algorithm for cluster architectures of wireless sensor networks; the proposed algorithm reconstructs the nodes based on side information. Simulation analysis shows that the improved distributed compressed sensing algorithm not only can access to the accurate reconstruction of the nodes, but also can reduce energy consumption during the process of algorithm greatly.

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Published
2014-06-15
How to Cite
JIANG, Nan et al. Distributed Compressed Sensing Algorithm for Cluster Architectures of WSNs. INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL, [S.l.], v. 9, n. 4, p. 430-438, june 2014. ISSN 1841-9844. Available at: <http://univagora.ro/jour/index.php/ijccc/article/view/242>. Date accessed: 23 sep. 2020. doi: https://doi.org/10.15837/ijccc.2014.4.242.

Keywords

Wireless sensor networks, distributed compressed sensing, joint sparsity models, LEACH protocol, side information