Mapping and scheduling for non-uniform arrival of virtual network function (VNF) requests

Gamal, M; Jafarizadeh, S; Abolhasan, M; Lipman, J; Ni, W

Mapping and scheduling for non-uniform arrival of virtual network function (VNF) requests

Gamal, M Jafarizadeh, S Abolhasan, M

Lipman, J

Ni, W

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Publication Type:: Conference Proceeding
Citation:: IEEE Vehicular Technology Conference, 2019, 2019-September
Issue Date:: 2019-09-01

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Field	Value	Language
dc.contributor.author	Gamal, M	en_US
dc.contributor.author	Jafarizadeh, S	en_US
dc.contributor.author	Abolhasan, M https://orcid.org/0000-0002-4282-6666	en_US
dc.contributor.author	Lipman, J https://orcid.org/0000-0003-2877-1168	en_US
dc.contributor.author	Ni, W	en_US
dc.date.accessioned	2020-04-07T14:17:13Z
dc.date.available	2020-04-07T14:17:13Z
dc.date.issued	2019-09-01	en_US
dc.identifier.citation	IEEE Vehicular Technology Conference, 2019, 2019-September	en_US
dc.identifier.isbn	9781728112206	en_US
dc.identifier.issn	1550-2252	en_US
dc.identifier.uri	http://hdl.handle.net/10453/139872
dc.description.abstract	© 2019 IEEE. As a new research concept for both academia and industry, there are several challenges faced by the Network Function Virtualization (NFV). One such challenge is to find the optimal mapping and scheduling for the incoming service requests which is the focus of this study. This optimization has been done by maximizing the number of accepted service requests, minimizing the number of bottleneck links and the overall processing time. The resultant problem is formulated as a multi- objective optimization problem, and two novel algorithms based on genetic algorithm have been developed. Through simulations, it has been shown that the developed algorithms can converge to the near to optimal solutions and they are scalable to large networks.	en_US
dc.relation.ispartof	IEEE Vehicular Technology Conference	en_US
dc.relation.isbasedon	10.1109/VTCFall.2019.8891197	en_US
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Mapping and scheduling for non-uniform arrival of virtual network function (VNF) requests	en_US
dc.type	Conference Proceeding
utslib.citation.volume	2019-September	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
utslib.copyright.status	closed_access	*
pubs.publication-status	Published	en_US
pubs.volume	2019-September	en_US

Abstract:

© 2019 IEEE. As a new research concept for both academia and industry, there are several challenges faced by the Network Function Virtualization (NFV). One such challenge is to find the optimal mapping and scheduling for the incoming service requests which is the focus of this study. This optimization has been done by maximizing the number of accepted service requests, minimizing the number of bottleneck links and the overall processing time. The resultant problem is formulated as a multi- objective optimization problem, and two novel algorithms based on genetic algorithm have been developed. Through simulations, it has been shown that the developed algorithms can converge to the near to optimal solutions and they are scalable to large networks.

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http://hdl.handle.net/10453/139872