Enabling dynamic autoscaling for NFV in a non-standalone virtual EPC: Design and analysis

Ren, Yi ORCID: https://orcid.org/0000-0001-7423-6719, Phung-duc, Tuan, Chen, Jyh-cheng and Li, Frank Y. (2023) Enabling dynamic autoscaling for NFV in a non-standalone virtual EPC: Design and analysis. IEEE Transactions on Vehicular Technology. pp. 1-14. ISSN 0018-9545

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Network function virtualization (NFV) is a novel concept that enables an architectural transition from dedicated hardware to orchestrated resource and function management. As an integral part of the core network, NFV offers a fine-grained network capability to cellular operators by scaling out or scaling in network resources in an on-demand manner to meet the performance requirements. However, designing an autoscaling algorithm with low operation cost and low latency in non-standalone networks, where legacy network equipment coexists with a virtual evolved packet core (EPC), is a challenging task. In this paper, we propose a dynamic NFV instance autoscaling algorithm that considers the tradeoff between performance and operation cost. Furthermore, we develop an analytical framework to assess the performance of the scheme by modeling the hybrid network as a queueing system that includes both legacy network equipment and NFV instances. The virtualized network function (VNF) instances are powered on or off according to the number of job requests. Numerical results based on extensive simulations validate the correctness of the model and the effectiveness of the algorithm.

Item Type: Article
Uncontrolled Keywords: 5g mobile communication,computational modeling,costs,epc,hardware,heuristic algorithms,nfv instance resource allocation,network function virtualization,resource management,dynamic autoscaling algorithm,modeling and analysis,network function virtualization,automotive engineering,aerospace engineering,electrical and electronic engineering,applied mathematics ,/dk/atira/pure/subjectarea/asjc/2200/2203
Faculty \ School: Faculty of Science > School of Computing Sciences
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Depositing User: LivePure Connector
Date Deposited: 16 Feb 2023 16:31
Last Modified: 31 Mar 2023 15:30
URI: https://ueaeprints.uea.ac.uk/id/eprint/91163
DOI: 10.1109/TVT.2023.3237698

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