An iteratively tuned fuzzy logic movement model in WSN using particle swarm optimization

Rafiei, A; Maali, Y; Abolhasan, M; Franklin, D; Smith, S

An iteratively tuned fuzzy logic movement model in WSN using particle swarm optimization

Rafiei, A Maali, Y Abolhasan, M

Franklin, D

Smith, S

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Publication Type:: Conference Proceeding
Citation:: 2013, 7th International Conference on Signal Processing and Communication Systems, ICSPCS 2013 - Proceedings, 2013
Issue Date:: 2013-01-01

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Field	Value	Language
dc.contributor.author	Rafiei, A	en_US
dc.contributor.author	Maali, Y	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	Smith, S	en_US
dc.date.issued	2013-01-01	en_US
dc.identifier.citation	2013, 7th International Conference on Signal Processing and Communication Systems, ICSPCS 2013 - Proceedings, 2013	en_US
dc.identifier.isbn	9781479913190	en_US
dc.identifier.uri	http://hdl.handle.net/10453/120172
dc.description.abstract	In contrast to adding new nodes, relocation of deployed nodes in mobile wireless sensor networks seems to be an effective solution to cope with undesirable, unpredictable and uncontrolled network topology changes due to nodes' drift and failure. At the price of less global control, there is a trend in recent years towards giving nodes more autonomy and devising localized relocation algorithms to address challenges of network topology control in harsh and hostile environments in the absence of centralized control. Inspired by laws of nature, a large variety of distributed node relocation algorithms have been designed to alleviate undesirable oscillations caused by local interactions and uncertainties among autonomous nodes as they reach their desired formations. Force-based distributed relocation algorithms governed by virtual push-pull forces among autonomous nodes are among such aforesaid algorithms. Adapting fuzzy logic model in exerting proper amount of forces to reduce node movement oscillation seems to be promising as its conforms well with uncertainties and interactions of autonomous nodes. However, parameters of fuzzy logic relocation model should be tuned so to enable nodes to exert proper amount of forces among their in-range neighbours. In this paper, by using particle swarm optimization, parameters of fuzzy relocation model are obtained based on the desired combinations of performance metrics within nodes' range in each movement iteration. The result shows that our model either outperforms or matches DSSA movement model. © 2013 IEEE.	en_US
dc.relation	http://purl.org/au-research/grants/arc/DP0879507
dc.relation.ispartof	2013, 7th International Conference on Signal Processing and Communication Systems, ICSPCS 2013 - Proceedings	en_US
dc.relation.isbasedon	10.1109/ICSPCS.2013.6723941	en_US
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	An iteratively tuned fuzzy logic movement model in WSN using particle swarm optimization	en_US
dc.type	Conference Proceeding
utslib.for	0805 Distributed Computing	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:

In contrast to adding new nodes, relocation of deployed nodes in mobile wireless sensor networks seems to be an effective solution to cope with undesirable, unpredictable and uncontrolled network topology changes due to nodes' drift and failure. At the price of less global control, there is a trend in recent years towards giving nodes more autonomy and devising localized relocation algorithms to address challenges of network topology control in harsh and hostile environments in the absence of centralized control. Inspired by laws of nature, a large variety of distributed node relocation algorithms have been designed to alleviate undesirable oscillations caused by local interactions and uncertainties among autonomous nodes as they reach their desired formations. Force-based distributed relocation algorithms governed by virtual push-pull forces among autonomous nodes are among such aforesaid algorithms. Adapting fuzzy logic model in exerting proper amount of forces to reduce node movement oscillation seems to be promising as its conforms well with uncertainties and interactions of autonomous nodes. However, parameters of fuzzy logic relocation model should be tuned so to enable nodes to exert proper amount of forces among their in-range neighbours. In this paper, by using particle swarm optimization, parameters of fuzzy relocation model are obtained based on the desired combinations of performance metrics within nodes' range in each movement iteration. The result shows that our model either outperforms or matches DSSA movement model. © 2013 IEEE.

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http://hdl.handle.net/10453/120172