TY - JOUR
T1 - Obstacle detection and estimation in wireless sensor networks
AU - Wang, Wei Tong
AU - Ssu, Kuo Feng
N1 - Funding Information:
The authors would like to thank the anonymous reviewers and the editors for the valuable suggestions that improved this paper. This research was supported in part by the Taiwan National Science Council (NSC) under Contracts NSC 100-2628-E-006-028-MY3, 100-2221-E-006-136-MY2, and 101-2221-E-006-247-MY3.
PY - 2013/3/13
Y1 - 2013/3/13
N2 - In wireless sensor networks (WSNs), it is likely that a deployed area contains obstacles of some form. These obstacles may potentially degrade the functionality of the WSN. If the size and location of the obstacles can be detected, their influence can be reduced. Accordingly, this paper describes a scheme for detecting obstacles in WSNs. The scheme identifies the obstacles by marking the sensor nodes around the obstacle boundaries. The scheme does not require the absolute position of individual nodes in the sensing field nor any additional hardware, and thus can significantly reduce the deployment costs. The efficiency of the scheme is demonstrated via simulations performed using the network simulator ns-2. The results show that the detection scheme needs much less overhead compared to previous research while still marking the nodes close to the obstacles precisely.
AB - In wireless sensor networks (WSNs), it is likely that a deployed area contains obstacles of some form. These obstacles may potentially degrade the functionality of the WSN. If the size and location of the obstacles can be detected, their influence can be reduced. Accordingly, this paper describes a scheme for detecting obstacles in WSNs. The scheme identifies the obstacles by marking the sensor nodes around the obstacle boundaries. The scheme does not require the absolute position of individual nodes in the sensing field nor any additional hardware, and thus can significantly reduce the deployment costs. The efficiency of the scheme is demonstrated via simulations performed using the network simulator ns-2. The results show that the detection scheme needs much less overhead compared to previous research while still marking the nodes close to the obstacles precisely.
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U2 - 10.1016/j.comnet.2012.11.004
DO - 10.1016/j.comnet.2012.11.004
M3 - Article
AN - SCOPUS:84875495516
SN - 1389-1286
VL - 57
SP - 858
EP - 868
JO - Computer Networks
JF - Computer Networks
IS - 4
ER -