Deep Reinforcement Learning-Based QoS Optimization for Software-Defined Factory Heterogeneous Networks-Reference-Cited by-同舟云学术

Deep Reinforcement Learning-Based QoS Optimization for Software-Defined Factory Heterogeneous Networks

Published:2022-12 Issue:4 Volume:19 Page:4058-4068
ISSN:1932-4537
Container-title:IEEE Transactions on Network and Service Management
language:
Short-container-title:IEEE Trans. Netw. Serv. Manage.

Author:

Xia Dan¹^ORCID,Wan Jiafu¹^ORCID,Xu Pengpeng²,Tan Jinbiao¹

Affiliation:

1. Guangdong Provincial Key Laboratory of Technique and Equipment for Macromolecular Advanced Manufacturing, School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou, China

2. Shien-Ming Wu School of Intelligent Engineering, South China University of Technology, Guangzhou, China

Funder

Guangdong Province Key Areas R & D Program

Joint Fund of the National Natural Science Foundation of China and Guangdong Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Networks and Communications

Link

http://xplorestaging.ieee.org/ielx7/4275028/10034788/09896990.pdf?arnumber=9896990

Reference32 articles.

1. Cross-Network Fusion and Scheduling for Heterogeneous Networks in Smart Factory

2. A novel industrial control architecture based on Software-Defined Network

3. Adaptive Transmission Optimization in SDN-Based Industrial Internet of Things With Edge Computing

4. Software-Defined Industrial Internet of Things in the Context of Industry 4.0

5. RL-Routing: An SDN Routing Algorithm Based on Deep Reinforcement Learning

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