Multi-objective VNF Placement Optimization with NSGA-III

Bekhit, M; Fathalla, A; Eldesouky, E; Salah, A

Multi-objective VNF Placement Optimization with NSGA-III

Bekhit, M

Fathalla, A Eldesouky, E Salah, A

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Publisher:: Springer Nature
Publication Type:: Conference Proceeding
Citation:: Lecture Notes in Networks and Systems, 2023, 700 LNNS, pp. 481-493
Issue Date:: 2023-01-01

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Field	Value	Language
dc.contributor.author	Bekhit, M https://orcid.org/0000-0002-8115-4233
dc.contributor.author	Fathalla, A
dc.contributor.author	Eldesouky, E
dc.contributor.author	Salah, A
dc.date.accessioned	2024-02-05T07:15:57Z
dc.date.available	2024-02-05T07:15:57Z
dc.date.issued	2023-01-01
dc.identifier.citation	Lecture Notes in Networks and Systems, 2023, 700 LNNS, pp. 481-493
dc.identifier.isbn	9783031337420
dc.identifier.issn	2367-3370
dc.identifier.issn	2367-3389
dc.identifier.uri	http://hdl.handle.net/10453/175304
dc.description.abstract	With the rising acceptance of virtual network functions (VNFs) as a replacement for traditional network functions, the optimal placement of VNFs has become a crucial task for ensuring constant performance within constrained resources. This research investigates the challenge of mapping and scheduling VNFs as a multi-objective optimization problem. The state-of-the-art methods have focused on optimizing the mapping or scheduling of VNFs while considering one or two objectives continuously. In this study, we aim to optimize two objectives: minimizing the link capacity cost and maximizing the average resource utilization of each virtual machine. To address this problem, an adaptation of the NSGA-III optimization algorithm is proposed and thoroughly evaluated through a set of experiments. In terms of objective values, the results outlined that the proposed method outperformed the other methods of comparison by a significant margin.
dc.language	en
dc.publisher	Springer Nature
dc.relation.ispartof	Lecture Notes in Networks and Systems
dc.relation.ispartofseries	Lecture Notes in Networks and Systems
dc.relation.isbasedon	10.1007/978-3-031-33743-7_39
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Multi-objective VNF Placement Optimization with NSGA-III
dc.type	Conference Proceeding
utslib.citation.volume	700 LNNS
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	closed_access	*
dc.date.updated	2024-02-05T07:15:56Z
pubs.publication-status	Published
pubs.volume	700 LNNS

Abstract:

With the rising acceptance of virtual network functions (VNFs) as a replacement for traditional network functions, the optimal placement of VNFs has become a crucial task for ensuring constant performance within constrained resources. This research investigates the challenge of mapping and scheduling VNFs as a multi-objective optimization problem. The state-of-the-art methods have focused on optimizing the mapping or scheduling of VNFs while considering one or two objectives continuously. In this study, we aim to optimize two objectives: minimizing the link capacity cost and maximizing the average resource utilization of each virtual machine. To address this problem, an adaptation of the NSGA-III optimization algorithm is proposed and thoroughly evaluated through a set of experiments. In terms of objective values, the results outlined that the proposed method outperformed the other methods of comparison by a significant margin.

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