Traffic Classification using Deep Learning Approach for End-to-End Slice Management in 5G/B5G-Reference-Cited by-同舟云学术

Traffic Classification using Deep Learning Approach for End-to-End Slice Management in 5G/B5G

Published:2022-10-19 Issue: Volume: Page:
ISSN:
Container-title:2022 13th International Conference on Information and Communication Technology Convergence (ICTC)
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Author:

Mohammedali Noor Abdalkarem¹,Kanakis Triantafyllos¹,Al-Sherbaz Ali²,Agyeman Michael Opoku¹

Affiliation:

1. University of Northampton,Centre for Smart and Advanced Technologies (CAST),Northampton,UK

2. School of Computing and Engineering, University of Gloucestershire,Gloucestershire,UK

Funder

Ministry of Higher Education and Scientific Research

University of Northampton

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9952188/9952355/09952446.pdf?arnumber=9952446

Reference25 articles.

1. System architecture and key technologies for 5G heterogeneous cloud radio access networks

2. Mobility management solutions for 5G networks: Architecture and services

3. 5G network slicing using SDN and NFV: A survey of taxonomy, architectures and future challenges

4. Network slicing games: Enabling customization in multi-tenant networks

5. An inter-slice management solution for future virtualization-based 5g systems;bordel;International Conference on Advanced Information Networking and Applications,2019

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