RLSK: A Job Scheduler for Federated Kubernetes Clusters based on Reinforcement Learning-Reference-Cited by-同舟云学术

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RLSK: A Job Scheduler for Federated Kubernetes Clusters based on Reinforcement Learning

Published:2020-04 Issue: Volume: Page:
ISSN:
Container-title:2020 IEEE International Conference on Cloud Engineering (IC2E)
language:
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Author:

Huang Jiaming,Xiao Chuming,Wu Weigang

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9094050/9096260/09096488.pdf?arnumber=9096488

Cited by 34 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. On the Optimization of Kubernetes toward the Enhancement of Cloud Computing;Mathematics;2024-08-10

2. Efficient Scaling on GPU for Federated Learning in Kubernetes: A Reinforcement Learning Approach;2024 International Technical Conference on Circuits/Systems, Computers, and Communications (ITC-CSCC);2024-07-02

3. A neural network framework for optimizing parallel computing in cloud servers;Journal of Systems Architecture;2024-05

4. CAROKRS: Cost-Aware Resource Optimization Kubernetes Resource Scheduler;2024 9th International Conference on Cloud Computing and Big Data Analytics (ICCCBDA);2024-04-25

5. A self-adaptive approach to job scheduling in cloud computing environments;SCI IRAN;2024

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