TY - GEN
T1 - Localization based on best spatial correlation distance mobility prediction for underwater wireless sensor networks
AU - Liu, Meiqin
AU - Guo, Xiaodong
AU - Zhang, Senlin
N1 - Publisher Copyright:
© 2015 Technical Committee on Control Theory, Chinese Association of Automation.
PY - 2015/9/11
Y1 - 2015/9/11
N2 - In order to reduce the communication cost while keeping the localization coverage and localization accuracy high, we propose a new localization scheme for underwater wireless sensor networks, i.e., localization based on best spatial correlation distance mobility prediction (LBMP). Nodes predict their mobility pattern by utilizing the spatial correlation between the mobility of underwater nodes and get located. In order to keep the localization error small, nodes with great computation ability calculate the best spatial correlation distance for the neighbor nodes to predict their mobility pattern. LBMP defines the confidence of a node to evaluate the accuracy of mobility pattern and location prediction. By controlling the value of the confidence threshold, LBMP can guarantee the quality of mobility pattern and location prediction. Simulation experiments show that, comparing to the scheme without the selection of best spatial correlation distance, LBMP has better performance in keeping relatively high localization coverage and localization accuracy while reducing communication cost apparently.
AB - In order to reduce the communication cost while keeping the localization coverage and localization accuracy high, we propose a new localization scheme for underwater wireless sensor networks, i.e., localization based on best spatial correlation distance mobility prediction (LBMP). Nodes predict their mobility pattern by utilizing the spatial correlation between the mobility of underwater nodes and get located. In order to keep the localization error small, nodes with great computation ability calculate the best spatial correlation distance for the neighbor nodes to predict their mobility pattern. LBMP defines the confidence of a node to evaluate the accuracy of mobility pattern and location prediction. By controlling the value of the confidence threshold, LBMP can guarantee the quality of mobility pattern and location prediction. Simulation experiments show that, comparing to the scheme without the selection of best spatial correlation distance, LBMP has better performance in keeping relatively high localization coverage and localization accuracy while reducing communication cost apparently.
KW - best spatial correlation distance
KW - localization
KW - mobility pattern prediction
KW - nodes' confidence
KW - underwater wireless sensor networks
UR - https://www.scopus.com/pages/publications/84946569725
U2 - 10.1109/ChiCC.2015.7260883
DO - 10.1109/ChiCC.2015.7260883
M3 - 会议稿件
AN - SCOPUS:84946569725
T3 - Chinese Control Conference, CCC
SP - 7827
EP - 7832
BT - Proceedings of the 34th Chinese Control Conference, CCC 2015
A2 - Zhao, Qianchuan
A2 - Liu, Shirong
PB - IEEE Computer Society
T2 - 34th Chinese Control Conference, CCC 2015
Y2 - 28 July 2015 through 30 July 2015
ER -