AI-based Network Function Virtualization Orchestration

被引:0
|
作者
Kim, Hee-Gon [1 ]
Yoo, Jae-Hyoung [1 ]
Hong, James Won-Ki [1 ]
机构
[1] Pohang Univ Sci & Technol, Comp Sci & Engn, Pohang, South Korea
关键词
Network Orchestration; Network Function Virtualization; Machine Learning;
D O I
10.1109/NOMS59830.2024.10575048
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Network orchestration is pivotal in automating device, equipment, and service management within the network system. Currently, Network Function Virtualization (NFV) offers immense potential, but the challenge still lies in designing a capable orchestrator for dynamic networks. To address this challenge, we propose an AI-based NFV Orchestration Framework that leverages self-learning capabilities to detect dynamic network changes and make optimal decisions. This framework covers a range of essential functionalities, including NFV Orchestration, VNF Deployment, Service Function Chaining (SFC), Auto-Scaling, Migration, Anomaly Detection, Power Management, and Attack & Intrusion Detection. These functions collectively form a comprehensive ML-driven orchestration framework that offers adaptability, intelligence, and efficiency across the entire NFV environment. Our proposed structure aims for zero-touch automation, contributing to the efficient management of dynamic NFV network environments, and making it a compelling solution for the future of networking.
引用
收藏
页数:5
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