A fuzzy logic node relocation model in WSNs

Maali, Y; Rafiei, A; Abolhasan, M; Franklin, D; Safaei, F

A fuzzy logic node relocation model in WSNs

Maali, Y Rafiei, A Abolhasan, M

Franklin, D

Safaei, F

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Publication Type:: Conference Proceeding
Citation:: 6th International Conference on Signal Processing and Communication Systems, ICSPCS 2012 - Proceedings, 2012
Issue Date:: 2012-12-01

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Field	Value	Language
dc.contributor.author	Maali, Y	en_US
dc.contributor.author	Rafiei, A	en_US
dc.contributor.author	Abolhasan, M https://orcid.org/0000-0002-4282-6666	en_US
dc.contributor.author	Franklin, D https://orcid.org/0000-0002-9563-5943	en_US
dc.contributor.author	Safaei, F	en_US
dc.date.issued	2012-12-01	en_US
dc.identifier.citation	6th International Conference on Signal Processing and Communication Systems, ICSPCS 2012 - Proceedings, 2012	en_US
dc.identifier.isbn	9781467323932	en_US
dc.identifier.uri	http://hdl.handle.net/10453/22413
dc.description.abstract	Hostile and harsh environments may preclude the possibility of manual redeployment of new sensor nodes, especially in the areas suffering from widespread damage and unbalanced node deployments. Distributed local relocations of currently deployed nodes is one promising solution to this problem. By using expected global node density and force-based movement algorithms inspired by the laws of nature, it is possible to address the aforementioned challenge. Force-based movement algorithms steer nodes towards their new locations based on the aggregation of exerted virtual forces on the node from their neighborhood. Some implicit assumptions about nodes' global status such as expected global node density are not realistic in dynamic and harsh environments. Thus, to conform to the uncertain nature and local interactions of nodes, a combination of radial-angular force fuzzy movement algorithms is suggested. The performance of the proposed model in terms of percentage of coverage, uniformity and average movement under three different boundary conditions are evaluated and compared with distributed self-spreading algorithms (DSSA). The results show that the simple fuzzy movement algorithm either outperforms or matches DSSA even if nodes don't benefit from expected global node density as in DSSA. © 2012 IEEE.	en_US
dc.relation	http://purl.org/au-research/grants/arc/DP0879507
dc.relation.ispartof	6th International Conference on Signal Processing and Communication Systems, ICSPCS 2012 - Proceedings	en_US
dc.relation.isbasedon	10.1109/ICSPCS.2012.6507949	en_US
dc.title	A fuzzy logic node relocation model in WSNs	en_US
dc.type	Conference Proceeding
utslib.for	1099 Other Technology	en_US
dc.location.activity	Gold Coast, Australia	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
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Students
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

Hostile and harsh environments may preclude the possibility of manual redeployment of new sensor nodes, especially in the areas suffering from widespread damage and unbalanced node deployments. Distributed local relocations of currently deployed nodes is one promising solution to this problem. By using expected global node density and force-based movement algorithms inspired by the laws of nature, it is possible to address the aforementioned challenge. Force-based movement algorithms steer nodes towards their new locations based on the aggregation of exerted virtual forces on the node from their neighborhood. Some implicit assumptions about nodes' global status such as expected global node density are not realistic in dynamic and harsh environments. Thus, to conform to the uncertain nature and local interactions of nodes, a combination of radial-angular force fuzzy movement algorithms is suggested. The performance of the proposed model in terms of percentage of coverage, uniformity and average movement under three different boundary conditions are evaluated and compared with distributed self-spreading algorithms (DSSA). The results show that the simple fuzzy movement algorithm either outperforms or matches DSSA even if nodes don't benefit from expected global node density as in DSSA. © 2012 IEEE.

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http://hdl.handle.net/10453/22413