Socio-economic (Banking) model based algorithm for energy efficient routing in Wireless Sensor Networks

Sinha, S; Chaczko, Z

Socio-economic (Banking) model based algorithm for energy efficient routing in Wireless Sensor Networks

Sinha, S Chaczko, Z

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Publication Type:: Conference Proceeding
Citation:: BROADBANDCOM 2009 - Selected Papers on Broadband Communication, Information Technology and Biomedical Applications, 2009, pp. 195 - 201
Issue Date:: 2009-01-01

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Field	Value	Language
dc.contributor.author	Sinha, S	en_US
dc.contributor.author	Chaczko, Z https://orcid.org/0000-0002-2816-7510	en_US
dc.date.issued	2009-01-01	en_US
dc.identifier.citation	BROADBANDCOM 2009 - Selected Papers on Broadband Communication, Information Technology and Biomedical Applications, 2009, pp. 195 - 201	en_US
dc.identifier.isbn	9788374934701	en_US
dc.identifier.uri	http://hdl.handle.net/10453/11891
dc.description.abstract	Wireless Sensor Networks are typically characterized by very low-powered nodes performing data gathering, aggregation and routing tasks for very specific targets. The goal of such distributed network of nodes is essentially to work intelligently in data gathering, processing and routing in order to maximise the life-time of the network as a whole. Since these nodes are usually distributed in fairly inaccessible domains, such as a battlefield, bridges, tunnels, and other critical areas, it is not always easy to re-energize the nodes by replacing their battery source. So, the only other way to improve the service of such nodes is to minimize exchange of radio messages by optimizing routing and clustering algorithms. This paper introduces a new routing and clustering algorithm based on a popular and very familiar socioeconomic model 'the Banking Model.	en_US
dc.relation.ispartof	BROADBANDCOM 2009 - Selected Papers on Broadband Communication, Information Technology and Biomedical Applications	en_US
dc.title	Socio-economic (Banking) model based algorithm for energy efficient routing in Wireless Sensor Networks	en_US
dc.type	Conference Proceeding
utslib.for	0914 Resources Engineering and Extractive Metallurgy	en_US
dc.location.activity	Wroclaw, Poland	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
pubs.organisational-group	/University of Technology Sydney/Strength - INEXT - Innovation in IT Services and Applications
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

Wireless Sensor Networks are typically characterized by very low-powered nodes performing data gathering, aggregation and routing tasks for very specific targets. The goal of such distributed network of nodes is essentially to work intelligently in data gathering, processing and routing in order to maximise the life-time of the network as a whole. Since these nodes are usually distributed in fairly inaccessible domains, such as a battlefield, bridges, tunnels, and other critical areas, it is not always easy to re-energize the nodes by replacing their battery source. So, the only other way to improve the service of such nodes is to minimize exchange of radio messages by optimizing routing and clustering algorithms. This paper introduces a new routing and clustering algorithm based on a popular and very familiar socioeconomic model 'the Banking Model.

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http://hdl.handle.net/10453/11891