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

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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Enhancing Received Signal Strength-Based Localization through Coverage Hole Detection and Recovery. / Zhai, Shuangjiao; Tang, Zhanyong; Wang, Dajin et al.

In: Sensors, Vol. 18, No. 7, 2075, 2018.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Zhai, S, Tang, Z, Wang, D, Li, Q, Li, Z, Chen, X, Fang, D, Chen, F & Wang, Z 2018, 'Enhancing Received Signal Strength-Based Localization through Coverage Hole Detection and Recovery', Sensors, vol. 18, no. 7, 2075. https://doi.org/10.3390/s18072075

APA

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

Vancouver

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

Author

Zhai, Shuangjiao ; Tang, Zhanyong ; Wang, Dajin et al. / Enhancing Received Signal Strength-Based Localization through Coverage Hole Detection and Recovery. In: Sensors. 2018 ; Vol. 18, No. 7.

Bibtex

@article{a9683d01c862499682e19b45b980ec1f,
title = "Enhancing Received Signal Strength-Based Localization through Coverage Hole Detection and Recovery",
abstract = "In wireless sensor networks (WSNs), Radio Signal Strength Indicator (RSSI)-basedlocalization 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 thesensing 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.",
keywords = "wireless sensor networks, RSSI-based localization, coverage holes, Voronoi tessellation, Delaunay triangulation",
author = "Shuangjiao Zhai and Zhanyong Tang and Dajin Wang and Qingpei Li and Zhanglei Li and Xiaojiang Chen and Dingyi Fang and Feng Chen and Zheng Wang",
year = "2018",
doi = "10.3390/s18072075",
language = "English",
volume = "18",
journal = "Sensors",
issn = "1424-8220",
publisher = "Multidisciplinary Digital Publishing Institute (MDPI)",
number = "7",

}

RIS

TY - JOUR

T1 - Enhancing Received Signal Strength-Based Localization through Coverage Hole Detection and Recovery

AU - Zhai, Shuangjiao

AU - Tang, Zhanyong

AU - Wang, Dajin

AU - Li, Qingpei

AU - Li, Zhanglei

AU - Chen, Xiaojiang

AU - Fang, Dingyi

AU - Chen, Feng

AU - Wang, Zheng

PY - 2018

Y1 - 2018

N2 - In wireless sensor networks (WSNs), Radio Signal Strength Indicator (RSSI)-basedlocalization 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 thesensing 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.

AB - In wireless sensor networks (WSNs), Radio Signal Strength Indicator (RSSI)-basedlocalization 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 thesensing 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.

KW - wireless sensor networks

KW - RSSI-based localization

KW - coverage holes

KW - Voronoi tessellation

KW - Delaunay triangulation

U2 - 10.3390/s18072075

DO - 10.3390/s18072075

M3 - Journal article

VL - 18

JO - Sensors

JF - Sensors

SN - 1424-8220

IS - 7

M1 - 2075

ER -