Resource Demand Prediction for Network Slices in 5G Using ML Enhanced With Network Models-Reference-Cited by-同舟云学术

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Resource Demand Prediction for Network Slices in 5G Using ML Enhanced With Network Models

Published:2024-08 Issue:8 Volume:73 Page:11848-11861
ISSN:0018-9545
Container-title:IEEE Transactions on Vehicular Technology
language:
Short-container-title:IEEE Trans. Veh. Technol.

Author:

Garrido Luis A.¹^ORCID,Dalgkitsis Anestis¹^ORCID,Ramantas Kostas¹^ORCID,Ksentini Adlen²^ORCID,Verikoukis Christos³^ORCID

Affiliation:

1. R&D Department of Iquadrat Informatica S.L., Barcelona, Spain

2. Communication Systems Department of EURECOM, Sophia Antipolis, France

3. Department of Computer Engineering and Informatics, University of Patras, Patras, Greece

Funder

5GMEDIAHUB

5GERA

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/25/10637911/10466724.pdf?arnumber=10466724

Reference56 articles.

1. System architecture for the 5G system (5GS),2018

2. AI-Based mechanism for the Predictive Resource Allocation of V2X related Network Services

3. Network Slicing in 5G: Survey and Challenges

4. Overbooking network slices through yield-driven end-to-end orchestration

5. The Disruptions of 5G on Data-Driven Technologies and Applications

Cited by 1 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. Utility-Driven End-to-End Network Slicing for Diverse IoT Users in MEC: A Multi-Agent Deep Reinforcement Learning Approach;Sensors;2024-08-28

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