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Enhancing Received Signal Strength-Based Localization through Coverage Hole Detection and Recovery

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School of Information Science and Technology, Northwest University, Xi’an 710127, China
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School of Computer Science, Montclair State University, Montclair, NJ 07043, USA
3
School of Computer Science & Technology, Xi’an University of Posts & Telecommunications, Xi’an 710121, China
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School of Computing and Communications, Lancaster University, Lancaster LA1 4WA, UK
*
Author to whom correspondence should be addressed.
This paper is an extended version of the conference paper, Shuangjiao Zhai; Zhanyong Tang; Dajin Wang; Zhanglei Li; Xiaojiang Chen; Dingyi Fang; Feng Chen; Coverage Hole Detection and Recovery in Wireless Sensor Networks Based on RSSI-Based Localization, 2017 IEEE International Conference on Computational Science and Engineering (CSE) and IEEE International Conference on Embedded and Ubiquitous Computing (EUC), Guangzhou, China, 21–24 July 2017.
Sensors 2018, 18(7), 2075; https://doi.org/10.3390/s18072075
Received: 16 May 2018 / Revised: 14 June 2018 / Accepted: 22 June 2018 / Published: 28 June 2018
(This article belongs to the Section Sensor Networks)
In wireless sensor networks (WSNs), Radio Signal Strength Indicator (RSSI)-based localization techniques have been widely used in various applications, such as intrusion detection, battlefield surveillance, and animal monitoring. One fundamental performance measure in those applications is the sensing coverage of WSNs. Insufficient coverage will significantly reduce the effectiveness of the applications. However, most existing studies on coverage assume that the sensing range of a sensor node is a disk, and the disk coverage model is too simplistic for many localization techniques. Moreover, there are some localization techniques of WSNs whose coverage model is non-disk, such as RSSI-based localization techniques. In this paper, we focus on detecting and recovering coverage holes of WSNs to enhance RSSI-based localization techniques whose coverage model is an ellipse. We propose an algorithm inspired by Voronoi tessellation and Delaunay triangulation to detect and recover coverage holes. Simulation results show that our algorithm can recover all holes and can reach any set coverage rate, up to 100% coverage. View Full-Text
Keywords: wireless sensor networks; RSSI-based localization; coverage holes; Voronoi tessellation; Delaunay triangulation wireless sensor networks; RSSI-based localization; coverage holes; Voronoi tessellation; Delaunay triangulation
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MDPI and ACS Style

Zhai, S.; Tang, Z.; Wang, D.; Li, Q.; Li, Z.; Chen, X.; Fang, D.; Chen, F.; Wang, Z. Enhancing Received Signal Strength-Based Localization through Coverage Hole Detection and Recovery. Sensors 2018, 18, 2075. https://doi.org/10.3390/s18072075

AMA Style

Zhai S, Tang Z, Wang D, Li Q, Li Z, Chen X, Fang D, Chen F, Wang Z. Enhancing Received Signal Strength-Based Localization through Coverage Hole Detection and Recovery. Sensors. 2018; 18(7):2075. https://doi.org/10.3390/s18072075

Chicago/Turabian Style

Zhai, Shuangjiao, Zhanyong Tang, Dajin Wang, Qingpei Li, Zhanglei Li, Xiaojiang Chen, Dingyi Fang, Feng Chen, and Zheng Wang. 2018. "Enhancing Received Signal Strength-Based Localization through Coverage Hole Detection and Recovery" Sensors 18, no. 7: 2075. https://doi.org/10.3390/s18072075

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