Compressed network coding for distributed storage in Wireless Sensor Networks

Yang, X; Dutkiewicz, E; Cui, Q; Tao, X; Guo, YJ; Huang, X

Compressed network coding for distributed storage in Wireless Sensor Networks

Yang, X Dutkiewicz, E

Cui, Q Tao, X Guo, YJ

Huang, X

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Publication Type:: Conference Proceeding
Citation:: 2012 International Symposium on Communications and Information Technologies, ISCIT 2012, 2012, pp. 816 - 821
Issue Date:: 2012-12-01

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Field	Value	Language
dc.contributor.author	Yang, X	en_US
dc.contributor.author	Dutkiewicz, E https://orcid.org/0000-0002-4268-9286	en_US
dc.contributor.author	Cui, Q	en_US
dc.contributor.author	Tao, X	en_US
dc.contributor.author	Guo, YJ https://orcid.org/0000-0001-6008-9682	en_US
dc.contributor.author	Huang, X https://orcid.org/0000-0001-6869-5732	en_US
dc.date.issued	2012-12-01	en_US
dc.identifier.citation	2012 International Symposium on Communications and Information Technologies, ISCIT 2012, 2012, pp. 816 - 821	en_US
dc.identifier.isbn	9781467311571	en_US
dc.identifier.uri	http://hdl.handle.net/10453/119535
dc.description.abstract	Distributed storage plays a very important role in Wireless Sensor Networks (WSNs), especially in catastrophic scenarios. To improve the energy efficiency of distributed storage, this paper proposes a Compressed Network Coding based Distributed Storage (CNCDS) scheme. Exploiting the correlation of sensor readings and utilizing the Compressed Sensing (CS) theory and network coding technology, the proposed CNCDS scheme achieves good energy efficiency by reducing the number of transmissions and receptions. Theoretical analysis proves that, the measurement matrix of CNCDS scheme guarantees good CS recovery performance. Simulation results show that, compared with the conventional ICStorage scheme, the proposed CNCDS scheme reduces the number of transmissions, the number of receptions and the CS recovery mean squared error (MSE) by up to 55%, 74% and 76% respectively. In contrast to the conventional NICStorage scheme, the proposed CNCDS scheme can simultaneously reduce the number of transmissions, receptions and recovery MSE. © 2012 IEEE.	en_US
dc.relation.ispartof	2012 International Symposium on Communications and Information Technologies, ISCIT 2012	en_US
dc.relation.isbasedon	10.1109/ISCIT.2012.6381014	en_US
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Compressed network coding for distributed storage in Wireless Sensor Networks	en_US
dc.type	Conference Proceeding
utslib.for	0906 Electrical and Electronic Engineering	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 - GBDTC - Global Big Data Technologies
utslib.copyright.status	closed_access	*
pubs.publication-status	Published	en_US

Abstract:

Distributed storage plays a very important role in Wireless Sensor Networks (WSNs), especially in catastrophic scenarios. To improve the energy efficiency of distributed storage, this paper proposes a Compressed Network Coding based Distributed Storage (CNCDS) scheme. Exploiting the correlation of sensor readings and utilizing the Compressed Sensing (CS) theory and network coding technology, the proposed CNCDS scheme achieves good energy efficiency by reducing the number of transmissions and receptions. Theoretical analysis proves that, the measurement matrix of CNCDS scheme guarantees good CS recovery performance. Simulation results show that, compared with the conventional ICStorage scheme, the proposed CNCDS scheme reduces the number of transmissions, the number of receptions and the CS recovery mean squared error (MSE) by up to 55%, 74% and 76% respectively. In contrast to the conventional NICStorage scheme, the proposed CNCDS scheme can simultaneously reduce the number of transmissions, receptions and recovery MSE. © 2012 IEEE.

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http://hdl.handle.net/10453/119535