Deep Reinforcement Learning-based Edge Caching for Industrial Control Applications
Author:
Affiliation:
1. University of Posts and Telecommunications,College of Internet of Things Nanjing,Nanjing,China
2. PipeChina West East Gas Pipeline Company,Shanghai,China
3. University of Posts and Telecommunications,College of Automation Nanjing,Nanjing,China
Funder
National Natural Science Foundation of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10326447/10326467/10327657.pdf?arnumber=10327657
Reference15 articles.
1. A cache replacement algorithm for industrial edge computing applications(in Chinese);lei;Computer Research and Development,2021
2. Ultra-Low Latency (ULL) Networks: The IEEE TSN and IETF DetNet Standards and Related 5G ULL Research
3. A Reinforcement Learning-Based Replacement Strategy for Content Caching, GitHub repository;wang,2020
4. Human-level control through deep reinforcement learning
5. Deep Reinforcement Learning-Based Edge Caching in Wireless Networks
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