Balancing QoS and Security in the Edge: Existing Practices, Challenges, and 6G Opportunities With Machine Learning

Author:

Fadlullah Zubair Md1ORCID,Mao Bomin2ORCID,Kato Nei3ORCID

Affiliation:

1. Department of Computer Science, Lakehead University, Thunder Bay, Canada

2. School of Cybersecurity, Northwestern Polytechnical University, Xi’an, China

3. Graduate School of Information Sciences, Tohoku University, Sendai, Japan

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering

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1. Reviewing wireless broadband technologies in the peak smartphone era: 6G versus Wi-Fi 7 and 8;Telecommunications Policy;2024-07

2. Optimizing VNF Migration in B5G Core Networks: A Machine Learning Approach;2024 International Conference on Smart Applications, Communications and Networking (SmartNets);2024-05-28

3. Deep Learning-Based Throughput Prediction in 5G Cellular Networks;2024 International Conference on Smart Applications, Communications and Networking (SmartNets);2024-05-28

4. Fast Policy Convergence for Traffic Engineering with Proactive Distributed Message-Passing;2024 IEEE International Parallel and Distributed Processing Symposium (IPDPS);2024-05-27

5. A Secure Communicating While Jamming Approach for End-to-End Multi-Hop Wireless Communication Network;Chinese Journal of Electronics;2024-05

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