Scalability of Distributed Intelligence Architecture for 6G Network Automation-Reference-Cited by-同舟云学术

Scalability of Distributed Intelligence Architecture for 6G Network Automation

Published:2022-05-16 Issue: Volume: Page:
ISSN:
Container-title:ICC 2022 - IEEE International Conference on Communications
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Author:

Majumdar Sayantini¹,Trivisonno Riccardo¹,Carle Georg²

Affiliation:

1. Huawei Technologies,Munich Research Center

2. Technical University of Munich,Germany

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9837954/9838246/09838791.pdf?arnumber=9838791

Reference19 articles.

1. Efficient Auto-Scaling Approach in the Telco Cloud Using Self-Learning Algorithm

2. Deep Reinforcement Learning for Resource Management in Network Slicing

3. Deep Q-networks based Autoscaling for Service Function Chaining;lee;16th International Conference on Network and Service Management (CNSM 2010),2020

4. A Distributed Intelligence Architecture for B5G Network Automation;majumdar,2021

5. Understanding Exploration and Exploitation of Q-Learning Agents in B5G Network Management

Cited by 4 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. Distributing Intelligence for 6G Network Automation: Performance and Architectural Impact;ICC 2023 - IEEE International Conference on Communications;2023-05-28

2. Towards Massive Distribution of Intelligence for 6G Network Management using Double Deep Q-Networks;IEEE Transactions on Network and Service Management;2023

3. Improving Scalability of 6G Network Automation with Distributed Deep Q-Networks;GLOBECOM 2022 - 2022 IEEE Global Communications Conference;2022-12-04

4. Standardization Initiatives and Market Approaches in Edge Federation;2022 IEEE Conference on Standards for Communications and Networking (CSCN);2022-11-28