An Energy-Efficient Compressive Sensing-Based Clustering Routing Protocol for WSNs
A novel algorithm which combined the merits of the clustering strategy and the compressive sensing-based (CS-based) scheme was proposed in this paper. The lemmas for the relationship between any two adjacent layers, the optimal size of clusters, the optimal distribution of the cluster head (CH), and...
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| Published in | IEEE sensors journal Vol. 19; no. 10; pp. 3950 - 3960 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
IEEE
15.05.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1530-437X 1558-1748 |
| DOI | 10.1109/JSEN.2019.2893912 |
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| Abstract | A novel algorithm which combined the merits of the clustering strategy and the compressive sensing-based (CS-based) scheme was proposed in this paper. The lemmas for the relationship between any two adjacent layers, the optimal size of clusters, the optimal distribution of the cluster head (CH), and the corresponding proofs were presented first. In addition, to alleviate the "hot spot problem" and reduce the energy consumption resulted from the rotation of the role of CHs, a third role of backup CH (BCH) as well as the corresponding mechanism to rotate the roles between the CH and BCH were proposed. Subsequently, the energy-efficient compressive sensing-based clustering routing (EECSR) protocol was presented in detail. Finally, extensive simulation experiments were conducted to evaluate its energy performance. Comparisons with the existing clustering algorithms and the CS-based algorithm verified the effect of EECSR on improving energy efficiency and extending the lifespan of wireless sensor networks. |
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| AbstractList | A novel algorithm which combined the merits of the clustering strategy and the compressive sensing-based (CS-based) scheme was proposed in this paper. The lemmas for the relationship between any two adjacent layers, the optimal size of clusters, the optimal distribution of the cluster head (CH), and the corresponding proofs were presented first. In addition, to alleviate the "hot spot problem" and reduce the energy consumption resulted from the rotation of the role of CHs, a third role of backup CH (BCH) as well as the corresponding mechanism to rotate the roles between the CH and BCH were proposed. Subsequently, the energy-efficient compressive sensing-based clustering routing (EECSR) protocol was presented in detail. Finally, extensive simulation experiments were conducted to evaluate its energy performance. Comparisons with the existing clustering algorithms and the CS-based algorithm verified the effect of EECSR on improving energy efficiency and extending the lifespan of wireless sensor networks. A novel algorithm which combined the merits of the clustering strategy and the compressive sensing-based (CS-based) scheme was proposed in this paper. The lemmas for the relationship between any two adjacent layers, the optimal size of clusters, the optimal distribution of the cluster head (CH), and the corresponding proofs were presented first. In addition, to alleviate the “hot spot proble” and reduce the energy consumption resulted from the rotation of the role of CHs, a third role of backup CH (BCH) as well as the corresponding mechanism to rotate the roles between the CH and BCH were proposed. Subsequently, the energy-efficient compressive sensing-based clustering routing (EECSR) protocol was presented in detail. Finally, extensive simulation experiments were conducted to evaluate its energy performance. Comparisons with the existing clustering algorithms and the CS-based algorithm verified the effect of EECSR on improving energy efficiency and extending the lifespan of wireless sensor networks. |
| Author | Lin, Deyu Wang, Quan Yang, Pengfei Zhang, Zhiqiang |
| Author_xml | – sequence: 1 givenname: Quan surname: Wang fullname: Wang, Quan organization: School of Computer Science and Technology, Xidian University, Xi'an, China – sequence: 2 givenname: Deyu orcidid: 0000-0003-1400-4769 surname: Lin fullname: Lin, Deyu email: dashing_lin@126.com organization: School of Computer Science and Technology, Xidian University, Xi'an, China – sequence: 3 givenname: Pengfei surname: Yang fullname: Yang, Pengfei organization: School of Computer Science and Technology, Xidian University, Xi'an, China – sequence: 4 givenname: Zhiqiang surname: Zhang fullname: Zhang, Zhiqiang organization: School of Electronic and Electrical Engineering, University of Leeds, Leeds, U.K |
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| SubjectTerms | Algorithms Clustering Compressed sensing compressive sensing Computer simulation Correlation Detection Energy consumption Energy efficiency Redundancy Remote sensors Sensors the “hot spot problem” Wireless sensor networks |
| Title | An Energy-Efficient Compressive Sensing-Based Clustering Routing Protocol for WSNs |
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