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Localization from Connectivity in Sensor Networks
November 2004 (vol. 15 no. 11)
pp. 961-974
ASCII Text
x 
 
Yi Shang, Wheeler Ruml, Ying Zhang, Markus Fromherz, "Localization from Connectivity in Sensor Networks," IEEE Transactions on Parallel and Distributed Systems, vol. 15, no. 11, pp. 961-974, November, 2004.
 
 
BibTex
x
 
@article{ 10.1109/TPDS.2004.67,
author = {Yi Shang and Wheeler Ruml and Ying Zhang and Markus Fromherz},
title = {Localization from Connectivity in Sensor Networks},
journal ={IEEE Transactions on Parallel and Distributed Systems},
volume = {15},
number = {11},
issn = {1045-9219},
year = {2004},
pages = {961-974},
doi = {http://doi.ieeecomputersociety.org/10.1109/TPDS.2004.67},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Parallel and Distributed Systems
TI - Localization from Connectivity in Sensor Networks
IS - 11
SN - 1045-9219
SP961
EP974
EPD - 961-974
A1 - Yi Shang,
A1 - Wheeler Ruml,
A1 - Ying Zhang,
A1 - Markus Fromherz,
PY - 2004
KW - Wireless sensor networks
KW - optimization
KW - position estimation.
VL - 15
JA - IEEE Transactions on Parallel and Distributed Systems
ER -
 

Abstract—We propose an approach that uses connectivity information—who is within communications range of whom—to derive the locations of nodes in a network. The approach can take advantage of additional information, such as estimated distances between neighbors or known positions for certain anchor nodes, if it is available. It is based on multidimensional scaling (MDS), an efficient data analysis technique that takes O(n^3) time for a network of n nodes. Unlike previous approaches, MDS takes full advantage of connectivity or distance information between nodes that have yet to be localized. Two methods are presented: a simple method that builds a global map using MDS and a more complicated one that builds small local maps and then patches them together to form a global map. Furthermore, least-squares optimization can be incorporated into the methods to further improve the solutions at the expense of additional computation. Through simulation studies on uniform as well as irregular networks, we show that the methods achieve more accurate solutions than previous methods, especially when there are few anchor nodes. They can even yield good relative maps when no anchor nodes are available.

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Index Terms:
Wireless sensor networks, optimization, position estimation.
Citation:
Yi Shang, Wheeler Ruml, Ying Zhang, Markus Fromherz, "Localization from Connectivity in Sensor Networks," IEEE Transactions on Parallel and Distributed Systems, vol. 15, no. 11, pp. 961-974, Nov. 2004, doi:10.1109/TPDS.2004.67
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