Energy-Efficient Graph Reinforced vNFC Deployment in Elastic Optical Inter-DC Networks

Zhu, R; Zhang, W; Wang, P; Chen, J; Wang, J; Yu, S

Energy-Efficient Graph Reinforced vNFC Deployment in Elastic Optical Inter-DC Networks

Zhu, R Zhang, W Wang, P Chen, J Wang, J Yu, S

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Publisher:: Institute of Electrical and Electronics Engineers (IEEE)
Publication Type:: Journal Article
Citation:: IEEE Transactions on Network Science and Engineering, 2023, PP, (99), pp. 1-13
Issue Date:: 2023-01-01

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Field	Value	Language
dc.contributor.author	Zhu, R
dc.contributor.author	Zhang, W
dc.contributor.author	Wang, P
dc.contributor.author	Chen, J
dc.contributor.author	Wang, J
dc.contributor.author	Yu, S https://orcid.org/0000-0003-4485-6743
dc.date.accessioned	2024-03-12T01:13:18Z
dc.date.available	2024-03-12T01:13:18Z
dc.date.issued	2023-01-01
dc.identifier.citation	IEEE Transactions on Network Science and Engineering, 2023, PP, (99), pp. 1-13
dc.identifier.issn	2334-329X
dc.identifier.issn	2327-4697
dc.identifier.uri	http://hdl.handle.net/10453/176529
dc.description.abstract	With the rapid development of information and communication technology (ICT), the demand for flexible and cost-effective network services (NSs) is growing exponentially. Network function virtualization (NFV) based on elastic optical data center interconnections (EO-DCI) can provide flexible and timely NSs. One of the major concerns that draws the attention of researchers is the exponential growth of the energy consumption of the EO-DCI networks. Therefore, it is a practical issue to reduce the energy consumption of service deployment in EO-DCI networks while ensuring service success. In this paper, a flexible service provisioning based on virtual network function chain (vNFC) is exploited. Then we first formulate the energy-efficient vNFC deployment (EE-VNFD) problem in EO-DCI networks and propose an Integer Linear Programming (ILP) model of it by considering the four energy consumption components of CPUs, ports, transponders, and amplifiers. To obtain feasible solutions for real-scale problems, we propose an energy-efficient graph reinforced vNFC deployment (EGRD) algorithm based on reinforcement learning (RL) and graph convolutional networks (GCN). The performance of the EGRD algorithm is evaluated in both static and dynamic scenarios. In the static scenario, simulation results show that the EGRD algorithm achieves a near-optimal performance close to the ILP model. In the dynamic scenario, compared with two heuristic algorithms and two leading RL algorithms, the EGRD algorithm significantly reduces energy consumption in the resource-sufficient environment, and also balances energy consumption and blocking probability well in resource-limited environments.
dc.language	en
dc.publisher	Institute of Electrical and Electronics Engineers (IEEE)
dc.relation.ispartof	IEEE Transactions on Network Science and Engineering
dc.relation.isbasedon	10.1109/TNSE.2023.3325828
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Energy-Efficient Graph Reinforced vNFC Deployment in Elastic Optical Inter-DC Networks
dc.type	Journal Article
utslib.citation.volume	PP
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 Computer Science
pubs.organisational-group	University of Technology Sydney/Strength - CCSP - Centre for Cyber Security and Privacy
utslib.copyright.status	closed_access	*
dc.date.updated	2024-03-12T01:13:17Z
pubs.issue	99
pubs.publication-status	Published
pubs.volume	PP
utslib.citation.issue	99

Abstract:

With the rapid development of information and communication technology (ICT), the demand for flexible and cost-effective network services (NSs) is growing exponentially. Network function virtualization (NFV) based on elastic optical data center interconnections (EO-DCI) can provide flexible and timely NSs. One of the major concerns that draws the attention of researchers is the exponential growth of the energy consumption of the EO-DCI networks. Therefore, it is a practical issue to reduce the energy consumption of service deployment in EO-DCI networks while ensuring service success. In this paper, a flexible service provisioning based on virtual network function chain (vNFC) is exploited. Then we first formulate the energy-efficient vNFC deployment (EE-VNFD) problem in EO-DCI networks and propose an Integer Linear Programming (ILP) model of it by considering the four energy consumption components of CPUs, ports, transponders, and amplifiers. To obtain feasible solutions for real-scale problems, we propose an energy-efficient graph reinforced vNFC deployment (EGRD) algorithm based on reinforcement learning (RL) and graph convolutional networks (GCN). The performance of the EGRD algorithm is evaluated in both static and dynamic scenarios. In the static scenario, simulation results show that the EGRD algorithm achieves a near-optimal performance close to the ILP model. In the dynamic scenario, compared with two heuristic algorithms and two leading RL algorithms, the EGRD algorithm significantly reduces energy consumption in the resource-sufficient environment, and also balances energy consumption and blocking probability well in resource-limited environments.

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http://hdl.handle.net/10453/176529