Connectivity-based distance estimation in wireless sensor networks

Huang, B; Yu, C; Anderson, BDO; Mao, G

Connectivity-based distance estimation in wireless sensor networks

Huang, B Yu, C Anderson, BDO Mao, G

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Publication Type:: Conference Proceeding
Citation:: GLOBECOM - IEEE Global Telecommunications Conference, 2010
Issue Date:: 2010-12-01

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Field	Value	Language
dc.contributor.author	Huang, B	en_US
dc.contributor.author	Yu, C	en_US
dc.contributor.author	Anderson, BDO	en_US
dc.contributor.author	Mao, G https://orcid.org/0000-0002-3598-4949	en_US
dc.date.issued	2010-12-01	en_US
dc.identifier.citation	GLOBECOM - IEEE Global Telecommunications Conference, 2010	en_US
dc.identifier.isbn	9781424456383	en_US
dc.identifier.uri	http://hdl.handle.net/10453/29480
dc.description.abstract	Distance estimation is of great importance for localization and a variety of applications in wireless sensor networks. In this paper, we develop a simple and efficient method for estimating distances between any pairs of neighboring nodes in static wireless sensor networks based on their local connectivity information, namely the numbers of their common one-hop neighbors and non-common one-hop neighbors. The proposed method involves two steps: estimating an intermediate parameter through a Maximum-Likelihood Estimator (MLE) and then mapping this estimate to the associated distance estimate. In the first instance, we present the method by assuming that signal transmission satisfies the ideal unit disk model but then we expand it to the more realistic log-normal shadowing model. Finally, simulation results show that localization algorithms using the distance estimates produced by this method can deliver superior performances in most cases in comparison with the corresponding connectivity-based localization algorithms. ©2010 IEEE.	en_US
dc.relation.ispartof	GLOBECOM - IEEE Global Telecommunications Conference	en_US
dc.relation.isbasedon	10.1109/GLOCOM.2010.5683252	en_US
dc.title	Connectivity-based distance estimation in wireless sensor networks	en_US
dc.type	Conference Proceeding
utslib.for	0805 Distributed Computing	en_US
utslib.for	1005 Communications Technologies	en_US
dc.location.activity	Miami, FL	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CRIN - Realtime Information Networks
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

Distance estimation is of great importance for localization and a variety of applications in wireless sensor networks. In this paper, we develop a simple and efficient method for estimating distances between any pairs of neighboring nodes in static wireless sensor networks based on their local connectivity information, namely the numbers of their common one-hop neighbors and non-common one-hop neighbors. The proposed method involves two steps: estimating an intermediate parameter through a Maximum-Likelihood Estimator (MLE) and then mapping this estimate to the associated distance estimate. In the first instance, we present the method by assuming that signal transmission satisfies the ideal unit disk model but then we expand it to the more realistic log-normal shadowing model. Finally, simulation results show that localization algorithms using the distance estimates produced by this method can deliver superior performances in most cases in comparison with the corresponding connectivity-based localization algorithms. ©2010 IEEE.

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http://hdl.handle.net/10453/29480