Efficient Communication-Computation Tradeoff for Split Computing: A Multi-Tier Deep Reinforcement Learning Approach-Reference-Cited by-同舟云学术

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Efficient Communication-Computation Tradeoff for Split Computing: A Multi-Tier Deep Reinforcement Learning Approach

Published:2023-12-04 Issue: Volume: Page:1-6
ISSN:
Container-title:GLOBECOM 2023 - 2023 IEEE Global Communications Conference
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Author:

Cao Yang¹,Lien Shao-Yu²,Yeh Cheng-Hao³,Liang Ying-Chang¹,Niyato Dusit⁴

Affiliation:

1. Yangtze Delta Region Institute (Huzhou), University of Electronic Science and Technology of China,Huzhou,P. R. China

2. National Yang Ming Chiao Tung University,Tainan City,Taiwan

3. National Chung Cheng University,Chiayi,Taiwan

4. Nanyang Technological University,Singapore

Funder

Program of Introducing Talents of Discipline to Universities

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10436708/10436716/10437522.pdf?arnumber=10437522

Reference13 articles.

1. Distributed Artificial Intelligence Empowered by End-Edge-Cloud Computing: A Survey

2. Wireless Channel Adaptive DNN Split Inference for Resource-Constrained Edge Devices

3. Optimal Model Placement and Online Model Splitting for Device-Edge Co-Inference

4. Split Learning Over Wireless Networks: Parallel Design and Resource Management

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