TY - GEN
T1 - Locating sensors in the forest
T2 - IEEE Conference on Computer Communications, INFOCOM 2012
AU - Bo, Cheng
AU - Ren, Danping
AU - Tang, Shaojie
AU - Li, Xiang Yang
AU - Mao, Xufei
AU - Huang, Qiuyuan
AU - Mo, Lufeng
AU - Jiang, Zhiping
AU - Sun, Yongmei
AU - Liu, Yunhao
PY - 2012
Y1 - 2012
N2 - As a large scale real sensor network system, GreenOrbs reveals that locating sensor nodes in the forest still faces great challenges because of volatile and fluctuating environmental factors. In this paper, we present a novel localization scheme, EARL, which provides accurate reference nodes and good ranging quality. We exam the range quality along routing paths by taking complex environmental factors into account, such as forest density, temperature and humidity. To improve localization accuracy, we use power scanning technique to judge the accuracy reference nodes and further calibrate the bad nodes through reverse-localization. To overcome the error propagation, we assign different weights to the range measurement according to the ranging quality. We implemented our localization scheme in GreenOrbs testbed, and evaluate through extensive experiments. The results demonstrate that EARL outperforms the current localization approaches with better accuracy. The localization accuracy achieved by our method is around 20% higher than best existing methods.
AB - As a large scale real sensor network system, GreenOrbs reveals that locating sensor nodes in the forest still faces great challenges because of volatile and fluctuating environmental factors. In this paper, we present a novel localization scheme, EARL, which provides accurate reference nodes and good ranging quality. We exam the range quality along routing paths by taking complex environmental factors into account, such as forest density, temperature and humidity. To improve localization accuracy, we use power scanning technique to judge the accuracy reference nodes and further calibrate the bad nodes through reverse-localization. To overcome the error propagation, we assign different weights to the range measurement according to the ranging quality. We implemented our localization scheme in GreenOrbs testbed, and evaluate through extensive experiments. The results demonstrate that EARL outperforms the current localization approaches with better accuracy. The localization accuracy achieved by our method is around 20% higher than best existing methods.
UR - https://www.scopus.com/pages/publications/84861621110
U2 - 10.1109/INFCOM.2012.6195458
DO - 10.1109/INFCOM.2012.6195458
M3 - Conference contribution
AN - SCOPUS:84861621110
SN - 9781467307758
T3 - Proceedings - IEEE INFOCOM
SP - 1026
EP - 1034
BT - 2012 Proceedings IEEE INFOCOM, INFOCOM 2012
Y2 - 25 March 2012 through 30 March 2012
ER -