Efficient Deployment and Scheduling of Shared VNF Instances in Mobile Edge Computing Networks

Mobile edge computing (MEC) is considered a promising technology to provide low-latency services by keeping computing and other resources physically close to where they are needed. The functions implemented through network function virtualization (NFV) technology in MEC are called virtual network fu...

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Veröffentlicht in:IEEE internet of things journal 2024-10, Vol.11 (19), p.32259-32271
Hauptverfasser: Li, Guoxin, Chen, Honglong, Wu, Liantao, Chi, Xuejian, Yao, Junmei, Xia, Feng, Yu, Jiguo
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Sprache:eng
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Zusammenfassung:Mobile edge computing (MEC) is considered a promising technology to provide low-latency services by keeping computing and other resources physically close to where they are needed. The functions implemented through network function virtualization (NFV) technology in MEC are called virtual network function (VNF) instances, and the deployment and scheduling of VNF instances have always been a hot topic. The deployment refers to deploying instances on the edge servers, while scheduling refers to allocating resources to complete user requests. However, most of the existing works fail to jointly consider the deployment and scheduling of VNF instances, which cannot complete user requests reasonably and efficiently. Besides, the deployment cost can be significantly reduced by making users share the same type of instances instead of assigning one to each user. Therefore, the objective of our article is to investigate the efficient deployment and scheduling of VNF instances that are shared among different users under constraints of user delay and network resources. We first build a VNF instance deployment and scheduling model in MEC networks to study how to minimize cost and maximize network throughput under the constraints of user delay and the computing and storage resources of cloudlets. Then, taking advantage of its sharing feature, we propose a set covering-based efficient deployment and scheduling scheme called SCEDS and evaluate its performance by extensive simulations. The simulation results demonstrate the superiority of our proposed method compared to the existing ones.
ISSN:2327-4662
2327-4662
DOI:10.1109/JIOT.2024.3424575