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2009 Ninth Annual International Symposium on Applications and the Internet
Measurement Analysis of the Live E! Sensor Network: Spatial-Temporal Correlations and Data Aggregation
Bellevue, Washington, USA
July 20-July 24
ISBN: 978-0-7695-3700-9
ASCII Text
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Elyes Ben Hamida, Hideya Ochiai, Hiroshi Esaki, Pierre Borgnat, Patrice Abry, Eric Fleury, "Measurement Analysis of the Live E! Sensor Network: Spatial-Temporal Correlations and Data Aggregation," Applications and the Internet, IEEE/IPSJ International Symposium on, pp. 263-266, 2009 Ninth Annual International Symposium on Applications and the Internet, 2009.
 
 
BibTex
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@article{ 10.1109/SAINT.2009.60,
author = {Elyes Ben Hamida and Hideya Ochiai and Hiroshi Esaki and Pierre Borgnat and Patrice Abry and Eric Fleury},
title = {Measurement Analysis of the Live E! Sensor Network: Spatial-Temporal Correlations and Data Aggregation},
journal ={Applications and the Internet, IEEE/IPSJ International Symposium on},
volume = {0},
year = {2009},
isbn = {978-0-7695-3700-9},
pages = {263-266},
doi = {http://doi.ieeecomputersociety.org/10.1109/SAINT.2009.60},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Applications and the Internet, IEEE/IPSJ International Symposium on
TI - Measurement Analysis of the Live E! Sensor Network: Spatial-Temporal Correlations and Data Aggregation
SN - 978-0-7695-3700-9
SP263
EP266
A1 - Elyes Ben Hamida,
A1 - Hideya Ochiai,
A1 - Hiroshi Esaki,
A1 - Pierre Borgnat,
A1 - Patrice Abry,
A1 - Eric Fleury,
PY - 2009
KW - Wireless sensor networks
KW - time series analysis
KW - time series decomposition
KW - temporal and spatial correlation
KW - data aggregation
VL - 0
JA - Applications and the Internet, IEEE/IPSJ International Symposium on
ER -
 
The (Japanese) Live E! project consists of a large sensor network of spatially distributed weather stations measuring different environmental quantities such as temperature, humidity, pressure, etc. Our goal is to conduct the first analysis on this huge data set of the structures of correlations both in time and space observed on data, for given quantity among stations, and for a given station, among sensors. Finally, we investigate a data aggregation algorithm, based on polynomial regression, and we show how it can reduce significatively the overall data traffic.
Index Terms:
Wireless sensor networks, time series analysis, time series decomposition, temporal and spatial correlation, data aggregation
Citation:
Elyes Ben Hamida, Hideya Ochiai, Hiroshi Esaki, Pierre Borgnat, Patrice Abry, Eric Fleury, "Measurement Analysis of the Live E! Sensor Network: Spatial-Temporal Correlations and Data Aggregation," saint, pp.263-266, 2009 Ninth Annual International Symposium on Applications and the Internet, 2009
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