Disaster Protection for Service Function Chain Provisioning in EO-DCNs

Network function virtualization (NFV) in Elastic Optical Inter-DataCenter Networks (EO-DCNs) enables a flexible, adaptive, effective, and economic network services deployment and upgrade. However, it is facing critical threats from large-scale network failures due to natural disasters. This is drivi...

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Vydáno v:IEEE eTransactions on network and service management Ročník 20; číslo 3; s. 1
Hlavní autoři: Liu, Yuanhao, Zhou, Fen, Shang, Tao, Torres-Moreno, Juan-Manuel
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.09.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Adaptation models
Algorithms
Delays
Disaster management
Disaster resilience
Elastic Optical Inter-DataCenter Network (EO-DCN)
Heuristic algorithms
Heuristic methods
Integer programming
Mathematical models
Natural disasters
Network function virtualization
Network Function Virtualization (NFV)
Optical communication
Optical fiber networks
Power consumption
Power demand
Provisioning
Resilience
Resource management
Service Function Chain (SFC)
Virtual networks
ISSN:1932-4537, 1932-4537
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Shrnutí:Network function virtualization (NFV) in Elastic Optical Inter-DataCenter Networks (EO-DCNs) enables a flexible, adaptive, effective, and economic network services deployment and upgrade. However, it is facing critical threats from large-scale network failures due to natural disasters. This is driving the need for efficient network protection schemes of service function chain (SFC) provisioning. In this paper, we investigate the disaster-resilient SFC provisioning problem leveraging power-efficient path protection with distance-adaptive modulation format (MF) assignment, concerning virtual network function (VNF) placement, SFC mapping, path protection, constrained recovery delay, and spectrum allocation simultaneously. An integer linear program (ILP) model is formulated to jointly minimize power consumption and spectrum usage, subject to disaster resilience. A heuristic algorithm is further developed for the sake of scalability. Numerical simulation results demonstrate that the proposed disaster protection schemes enable saving up to 32.05% power consumption.
Bibliografie:ObjectType-Article-1
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ISSN:1932-4537
1932-4537
DOI:10.1109/TNSM.2023.3293815