DocumentCode :
1811916
Title :
A beacon-less location discovery scheme for wireless sensor networks
Author :
Fang, Lei ; Du, Wenliang ; Ning, Peng
Author_Institution :
Dept. of Electr. Eng., Syracuse Univ., NY, USA
Volume :
1
fYear :
2005
fDate :
13-17 March 2005
Firstpage :
161
Abstract :
In wireless sensor networks (WSNs), sensor location plays a critical role in many applications. Having a GPS receiver on every sensor node is costly. In the past, a number of location discovery schemes have been proposed. Most of these schemes share a common feature: they use some special nodes, called beacon nodes, which are assumed to know their own locations (e.g., through GPS receivers or manual configuration). Other sensors discover their locations based on the information provided by these beacon nodes. In this paper, we show that efficient location discovery can be achieved in sensor networks without using beacons. We propose a beacon-less location discovery scheme, based on the following observations: in practice, it is quite common that sensors are deployed in groups, i.e., sensors are put into n groups, and sensors in the same group are deployed together at the same deployment point (the deployment point is different from the sensors´ final resident location). Sensors from the same group can land in different locations, and those locations usually follow a probability distribution that can be known a priori. With this prior deployment knowledge, we show that sensors can discover their locations by observing the group memberships of its neighbors. We model the location discovery problem as a statistical estimation problem, and we use the maximum likelihood estimation method to estimate the location. We have conducted experiments to evaluate our scheme.
Keywords :
maximum likelihood estimation; radionavigation; statistical distributions; wireless sensor networks; GPS receiver; beacon-less location discovery scheme; maximum likelihood estimation method; probability distribution; sensor node; statistical estimation problem; wireless sensor networks; Application software; Costs; Global Positioning System; Maximum likelihood estimation; Personnel; Probability distribution; Routing protocols; Satellites; Sensor systems; Wireless sensor networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
INFOCOM 2005. 24th Annual Joint Conference of the IEEE Computer and Communications Societies. Proceedings IEEE
ISSN :
0743-166X
Print_ISBN :
0-7803-8968-9
Type :
conf
DOI :
10.1109/INFCOM.2005.1497888
Filename :
1497888
Link To Document :
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