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21st International Symposium on High Performance Computing Systems and Applications (HPCS'07)
Benefits of Clustering in Landmark-Aided Positioning Algorithms
Saskatoon, Saskatchewan, Canada
May 13-May 16
ISBN: 0-7695-2813-9
ASCII Text
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Balasubramaneyam Maniymaran, Muthucumaru Maheswaran, Yuanyuan Gao, "Benefits of Clustering in Landmark-Aided Positioning Algorithms," High Performance Computing Systems and Applications, Annual International Symposium on, pp. 29, 21st International Symposium on High Performance Computing Systems and Applications (HPCS'07), 2007.
 
 
BibTex
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@article{ 10.1109/HPCS.2007.10,
author = {Balasubramaneyam Maniymaran and Muthucumaru Maheswaran and Yuanyuan Gao},
title = {Benefits of Clustering in Landmark-Aided Positioning Algorithms},
journal ={High Performance Computing Systems and Applications, Annual International Symposium on},
volume = {0},
year = {2007},
isbn = {0-7695-2813-9},
pages = {29},
doi = {http://doi.ieeecomputersociety.org/10.1109/HPCS.2007.10},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - High Performance Computing Systems and Applications, Annual International Symposium on
TI - Benefits of Clustering in Landmark-Aided Positioning Algorithms
SN - 0-7695-2813-9
SP
EP
A1 - Balasubramaneyam Maniymaran,
A1 - Muthucumaru Maheswaran,
A1 - Yuanyuan Gao,
PY - 2007
KW - null
VL - 0
JA - High Performance Computing Systems and Applications, Annual International Symposium on
ER -
 
Balasubramaneyam Maniymaran, McGill University, Montreal, QC, Canada
Muthucumaru Maheswaran, McGill University, Montreal, QC, Canada
Yuanyuan Gao, McGill University, Montreal, QC, Canada
In this paper, we propose simple and practical strategies to improve the trustworthiness of network positioning schemes. In particular, our strategies make network positioning immune to non-random perturbations such as denial-of-service attacks and localized network congestion. Additionally, we studied the overhead generated by existing network positioning algorithms and propose an algorithm that results in low overhead while retaining very high accuracies. We performed extensive simulations and implementations on PlanetLab to examine the performance trade-offs.
Citation:
Balasubramaneyam Maniymaran, Muthucumaru Maheswaran, Yuanyuan Gao, "Benefits of Clustering in Landmark-Aided Positioning Algorithms," hpcs, pp.29, 21st International Symposium on High Performance Computing Systems and Applications (HPCS'07), 2007
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