Application on self-provisioning of communication network service using fuzzy particle swarm optimization

Ling, SH; Jiang, F

Application on self-provisioning of communication network service using fuzzy particle swarm optimization

Ling, SH

Jiang, F

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Publication Type:: Conference Proceeding
Citation:: 2014 13th International Conference on Control Automation Robotics and Vision, ICARCV 2014, 2014, pp. 1245 - 1250
Issue Date:: 2014-01-01

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Field	Value	Language
dc.contributor.author	Ling, SH https://orcid.org/0000-0003-0849-5098	en_US
dc.contributor.author	Jiang, F	en_US
dc.date.issued	2014-01-01	en_US
dc.identifier.citation	2014 13th International Conference on Control Automation Robotics and Vision, ICARCV 2014, 2014, pp. 1245 - 1250	en_US
dc.identifier.isbn	9781479951994	en_US
dc.identifier.uri	http://hdl.handle.net/10453/41129
dc.description.abstract	© 2014 IEEE. In this paper, a self-provisioning of communication network service based on a fuzzy particle swarm optimization is proposed to minimize the configuration cost of four layer communication network. An swarm optimization called fuzzy particle swarm optimization (FPSO) is introduced. In this FPSO, the inertia weight of PSO is adaptively determined by a set of fuzzy rule. Also, a cross-mutated operation is presented to drive the solution to escape from local optima where the control parameter of this operation is also governed by a set of fuzzy rule. A performance comparison is given to show the performance of the proposed FPSO on the self-provisioning of communication network service and found that the performance of FPSO is significantly better than that of the existing hybrid PSO methods in a statistical sense.	en_US
dc.relation.ispartof	2014 13th International Conference on Control Automation Robotics and Vision, ICARCV 2014	en_US
dc.relation.isbasedon	10.1109/ICARCV.2014.7064494	en_US
dc.title	Application on self-provisioning of communication network service using fuzzy particle swarm optimization	en_US
dc.type	Conference Proceeding
utslib.for	080108 Neural, Evolutionary and Fuzzy Computation	en_US
dc.location.activity	Singapore
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 Biomedical Engineering
pubs.organisational-group	/University of Technology Sydney/Provost
pubs.organisational-group	/University of Technology Sydney/Provost/Jumbunna
pubs.organisational-group	/University of Technology Sydney/Strength - CHT - Health Technologies
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

© 2014 IEEE. In this paper, a self-provisioning of communication network service based on a fuzzy particle swarm optimization is proposed to minimize the configuration cost of four layer communication network. An swarm optimization called fuzzy particle swarm optimization (FPSO) is introduced. In this FPSO, the inertia weight of PSO is adaptively determined by a set of fuzzy rule. Also, a cross-mutated operation is presented to drive the solution to escape from local optima where the control parameter of this operation is also governed by a set of fuzzy rule. A performance comparison is given to show the performance of the proposed FPSO on the self-provisioning of communication network service and found that the performance of FPSO is significantly better than that of the existing hybrid PSO methods in a statistical sense.

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http://hdl.handle.net/10453/41129