Statistical analysis to extract effective parameters on overall energy consumption of Wireless Sensor Network (WSN)

Kamyabpour, N; Hoang, DB

Statistical analysis to extract effective parameters on overall energy consumption of Wireless Sensor Network (WSN)

Kamyabpour, N Hoang, DB

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Publication Type:: Conference Proceeding
Citation:: Parallel and Distributed Computing, Applications and Technologies, PDCAT Proceedings, 2012, pp. 20 - 23
Issue Date:: 2012-12-01

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Field	Value	Language
dc.contributor.author	Kamyabpour, N	en_US
dc.contributor.author	Hoang, DB https://orcid.org/0000-0003-1798-4926	en_US
dc.date.issued	2012-12-01	en_US
dc.identifier.citation	Parallel and Distributed Computing, Applications and Technologies, PDCAT Proceedings, 2012, pp. 20 - 23	en_US
dc.identifier.isbn	9780769548791	en_US
dc.identifier.uri	http://hdl.handle.net/10453/107830
dc.description.abstract	In this paper, we use statistical tools to analysis dependency between Wireless Sensor Network (WSN) parameters and overall Energy Consumption (EC). Our approach has two key steps: profiling, and effective parameter extraction. In former step, a sensor network simulator is re-run 800 times with different values of the WSN parameters to profile the average residual energy in nodes. In latter step, three statistical analyses (p-value, linear and non-linear correlation) are applied to the outcome of profiled experiments to extract the most effective parameters on WSN residual energy. © 2012 IEEE.	en_US
dc.relation.ispartof	Parallel and Distributed Computing, Applications and Technologies, PDCAT Proceedings	en_US
dc.relation.isbasedon	10.1109/PDCAT.2012.124	en_US
dc.title	Statistical analysis to extract effective parameters on overall energy consumption of Wireless Sensor Network (WSN)	en_US
dc.type	Conference Proceeding
utslib.for	080501 Distributed and Grid Systems	en_US
utslib.for	1006 Computer Hardware	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
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

In this paper, we use statistical tools to analysis dependency between Wireless Sensor Network (WSN) parameters and overall Energy Consumption (EC). Our approach has two key steps: profiling, and effective parameter extraction. In former step, a sensor network simulator is re-run 800 times with different values of the WSN parameters to profile the average residual energy in nodes. In latter step, three statistical analyses (p-value, linear and non-linear correlation) are applied to the outcome of profiled experiments to extract the most effective parameters on WSN residual energy. © 2012 IEEE.

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http://hdl.handle.net/10453/107830