TY - GEN
T1 - Coverage Hole Detection and Recovery in Wireless Sensor Networks Based on RSSI-Based Localization
AU - Zhai, Shuangjiao
AU - Tang, Zhanyong
AU - Wang, Dajin
AU - Li, Zhanglei
AU - Chen, Xiaojiang
AU - Fang, Dingyi
AU - Chen, Feng
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/8/8
Y1 - 2017/8/8
N2 - Wireless Sensor Networks (WSNs) based on RSSIbased 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 the target field. Most existing works on coverage assume that the sensing area of a sensor node is a disc. However, this disc model is too simplistic for many information processing systems, and there are sensing techniques whose sensing areas are non-disc. In this paper, we focus on coverage performance of WSNs based on RSSI-based localization techniques whose sensing area is an ellipse. We propose an algorithm inspired by Voronoi diagram 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, while using the minimum number of sensors.
AB - Wireless Sensor Networks (WSNs) based on RSSIbased 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 the target field. Most existing works on coverage assume that the sensing area of a sensor node is a disc. However, this disc model is too simplistic for many information processing systems, and there are sensing techniques whose sensing areas are non-disc. In this paper, we focus on coverage performance of WSNs based on RSSI-based localization techniques whose sensing area is an ellipse. We propose an algorithm inspired by Voronoi diagram 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, while using the minimum number of sensors.
KW - Coverage holes
KW - Delaunay Triangulation
KW - RSSI-based Localization
KW - Voronoi diagram
KW - Wireless Sensor Networks
UR - http://www.scopus.com/inward/record.url?scp=85034450025&partnerID=8YFLogxK
U2 - 10.1109/CSE-EUC.2017.231
DO - 10.1109/CSE-EUC.2017.231
M3 - Conference contribution
AN - SCOPUS:85034450025
T3 - Proceedings - 2017 IEEE International Conference on Computational Science and Engineering and IEEE/IFIP International Conference on Embedded and Ubiquitous Computing, CSE and EUC 2017
SP - 250
EP - 257
BT - Proceedings - 2017 IEEE International Conference on Computational Science and Engineering and IEEE/IFIP International Conference on Embedded and Ubiquitous Computing, CSE and EUC 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 20th IEEE International Conference on Computational Science and Engineering and 15th IEEE/IFIP International Conference on Embedded and Ubiquitous Computing, CSE and EUC 2017
Y2 - 21 July 2017 through 24 July 2017
ER -