Document Type
Article
Publication Date
7-1-2018
Journal / Book Title
Sensors
Abstract
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.
DOI
10.3390/s18072075
Montclair State University Digital Commons Citation
Zhai, Shuangjiao; Tang, Zhanyong; Wang, Dajin; Li, Qingpei; Li, Zhanglei; Chen, Xiaojiang; Fang, Dingyi; Chen, Feng; and Wang, Zheng, "Enhancing Received Signal Strength-Based Localization Through Coverage Hole Detection and Recovery" (2018). Department of Computer Science Faculty Scholarship and Creative Works. 267.
https://digitalcommons.montclair.edu/compusci-facpubs/267
Published Citation
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
Comments
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).