Machine Learning-Assisted Closed-Control Loops for Beyond 5G Multi-Domain Zero-Touch Networks

Author:

de Sousa Nathan Franklin SaraivaORCID,Islam Md Tariqul,Mustafa Raza Ul,Perez Danny Alex Lachos,Rothenberg Christian Esteve,Gomes Pedro Henrique

Funder

Innovation Center, Ericsson S.A.,Brazil,

Publisher

Springer Science and Business Media LLC

Subject

Strategy and Management,Computer Networks and Communications,Hardware and Architecture,Information Systems

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Autonomous Network Assurance in Intent Based Networking: Vision and Challenges;2023 32nd International Conference on Computer Communications and Networks (ICCCN);2023-07

2. Predicting XR Services QoE with ML: Insights from In-band Encrypted QoS Features in 360-VR;2023 IEEE 9th International Conference on Network Softwarization (NetSoft);2023-06-19

3. EFFECTOR: DASH QoE and QoS Evaluation Framework For EnCrypTed videO tRaffic;NOMS 2023-2023 IEEE/IFIP Network Operations and Management Symposium;2023-05-08

4. Deep-Learning-Based Blockchain for Secure Zero Touch Networks;IEEE Communications Magazine;2023-02

5. AutomAdapt: Zero Touch Configuration of 5G QoS Flows Extended for Time-Sensitive Networking;IEEE Access;2023

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