Optimizing Edge-Cloud Server Selection: A Multi-Objective Deep Reinforcement Learning Approach-Reference-Cited by-同舟云学术

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Optimizing Edge-Cloud Server Selection: A Multi-Objective Deep Reinforcement Learning Approach

Published:2024-06-27 Issue: Volume: Page:101-106
ISSN:
Container-title:2024 IEEE Cloud Summit
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Author:

Le Huyen-Trang¹,Tran Hai-Anh¹,Tran Truong X.²

Affiliation:

1. School of Information and Communications Technology, Hanoi University of Science and Technology (HUST),Hanoi,Vietnam

2. School of Science, Engineering and Technology Penn State Harrisburg, The Pennsylvania State University,Middletown,PA,United States,17057

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10630851/10630894/10630895.pdf?arnumber=10630895

Reference21 articles.

1. A Novel Load Balancing and Low Response Delay Framework for Edge-Cloud Network Based on SDN

2. Joint resource allocation and computation offloading in mobile edge computing for SDN based wireless networks

3. Pruning Pareto optimal solutions for multi-objective portfolio asset management

4. Network Resource Scheduling For Cloud/Edge Data Centers

5. Scalability and Performance Evaluation of Edge Cloud Systems for Latency Constrained Applications

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