Benefits of Clustering in Landmark-Aided Positioning Algorithms

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http://doi.ieeecomputersociety.org/10.1109/HPCS.2007.10

21st International Symposium on High ...

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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	x
	@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	x
	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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