TY - GEN
T1 - Graph Theory Based Localization of Wireless Sensor Networks for Radio Irregularity Cases
AU - Ma, Xiaofeng
AU - Yu, Ning
AU - Zhou, Tianle
AU - Feng, Renjian
AU - Wu, Yinfeng
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/10/15
Y1 - 2020/10/15
N2 - In the aerospace applications, the cases of radio irregularity, obstacle, asymmetrical distribution are disadvantageous for node localization of wireless sensor networks. In this paper, the related principles and methods of Graph Theory is introduced to minimize the localization error caused by radio irregularity. The model of asymmetry communication is established based on Graph Theory. Through the analysis to communication path between nodes in directed network, solution schemes are put forward for locating nodes in case of asymmetric communication. The localization performance is compared in different scenes and conditions. For node localization with radio irregularity, the accuracy can be improved 10% by our solutions when the network topology is regular. While the network topology is irregular, the localization accuracy can also be improved when strongly connected graph comes into being.
AB - In the aerospace applications, the cases of radio irregularity, obstacle, asymmetrical distribution are disadvantageous for node localization of wireless sensor networks. In this paper, the related principles and methods of Graph Theory is introduced to minimize the localization error caused by radio irregularity. The model of asymmetry communication is established based on Graph Theory. Through the analysis to communication path between nodes in directed network, solution schemes are put forward for locating nodes in case of asymmetric communication. The localization performance is compared in different scenes and conditions. For node localization with radio irregularity, the accuracy can be improved 10% by our solutions when the network topology is regular. While the network topology is irregular, the localization accuracy can also be improved when strongly connected graph comes into being.
KW - asymmetry communication
KW - graph theory
KW - localization
KW - radio irregularity
KW - wireless sensor networks
UR - https://www.scopus.com/pages/publications/85098547174
U2 - 10.1109/ICSMD50554.2020.9261666
DO - 10.1109/ICSMD50554.2020.9261666
M3 - 会议稿件
AN - SCOPUS:85098547174
T3 - International Conference on Sensing, Measurement and Data Analytics in the Era of Artificial Intelligence, ICSMD 2020 - Proceedings
SP - 51
EP - 56
BT - International Conference on Sensing, Measurement and Data Analytics in the Era of Artificial Intelligence, ICSMD 2020 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 1st International Conference on Sensing, Measurement and Data Analytics in the Era of Artificial Intelligence, ICSMD 2020
Y2 - 15 October 2020 through 17 October 2020
ER -