Enhancing Received Signal Strength-Based Localization through Coverage Hole Detection and Recovery
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 sensi...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2018-06-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/18/7/2075 |
| _version_ | 1818011640428232704 |
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| author | Shuangjiao Zhai Zhanyong Tang Dajin Wang Qingpei Li Zhanglei Li Xiaojiang Chen Dingyi Fang Feng Chen Zheng Wang |
| author_facet | Shuangjiao Zhai Zhanyong Tang Dajin Wang Qingpei Li Zhanglei Li Xiaojiang Chen Dingyi Fang Feng Chen Zheng Wang |
| author_sort | Shuangjiao Zhai |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-14T06:10:12Z |
| format | Article |
| id | doaj.art-3aa40b0605dd4714a22ed77a89475f96 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-14T06:10:12Z |
| publishDate | 2018-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-3aa40b0605dd4714a22ed77a89475f962022-12-22T02:08:23ZengMDPI AGSensors1424-82202018-06-01187207510.3390/s18072075s18072075Enhancing Received Signal Strength-Based Localization through Coverage Hole Detection and RecoveryShuangjiao Zhai0Zhanyong Tang1Dajin Wang2Qingpei Li3Zhanglei Li4Xiaojiang Chen5Dingyi Fang6Feng Chen7Zheng Wang8School of Information Science and Technology, Northwest University, Xi’an 710127, ChinaSchool of Information Science and Technology, Northwest University, Xi’an 710127, ChinaSchool of Computer Science, Montclair State University, Montclair, NJ 07043, USASchool of Information Science and Technology, Northwest University, Xi’an 710127, ChinaSchool of Information Science and Technology, Northwest University, Xi’an 710127, ChinaSchool of Information Science and Technology, Northwest University, Xi’an 710127, ChinaSchool of Information Science and Technology, Northwest University, Xi’an 710127, ChinaSchool of Information Science and Technology, Northwest University, Xi’an 710127, ChinaSchool of Computer Science & Technology, Xi’an University of Posts & Telecommunications, Xi’an 710121, ChinaIn 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.http://www.mdpi.com/1424-8220/18/7/2075wireless sensor networksRSSI-based localizationcoverage holesVoronoi tessellationDelaunay triangulation |
| spellingShingle | Shuangjiao Zhai Zhanyong Tang Dajin Wang Qingpei Li Zhanglei Li Xiaojiang Chen Dingyi Fang Feng Chen Zheng Wang Enhancing Received Signal Strength-Based Localization through Coverage Hole Detection and Recovery Sensors wireless sensor networks RSSI-based localization coverage holes Voronoi tessellation Delaunay triangulation |
| title | Enhancing Received Signal Strength-Based Localization through Coverage Hole Detection and Recovery |
| title_full | Enhancing Received Signal Strength-Based Localization through Coverage Hole Detection and Recovery |
| title_fullStr | Enhancing Received Signal Strength-Based Localization through Coverage Hole Detection and Recovery |
| title_full_unstemmed | Enhancing Received Signal Strength-Based Localization through Coverage Hole Detection and Recovery |
| title_short | Enhancing Received Signal Strength-Based Localization through Coverage Hole Detection and Recovery |
| title_sort | enhancing received signal strength based localization through coverage hole detection and recovery |
| topic | wireless sensor networks RSSI-based localization coverage holes Voronoi tessellation Delaunay triangulation |
| url | http://www.mdpi.com/1424-8220/18/7/2075 |
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