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Data-Driven Rate Control for RDMA Networks: A Lightweight Online Learning Approach

  • Published:2023-07 Issue: Volume: Page:
  • ISSN:
  • Container-title:2023 IEEE 43rd International Conference on Distributed Computing Systems (ICDCS)
  • language:
  • Short-container-title:

Author:

Ye Jiancheng1,Lin Dong1,Cai Kechao2,Zhou Chao3,He Jianfei4,Lui John C.S.5

Affiliation:

1. Huawei Technologies Co., Ltd.,Network Technology Lab and Hong Kong Research Center

2. School of Electronics and Communication Engineering, Sun Yat-Sen University,China

3. Computing Product Line, Huawei Technologies Co., Ltd.

4. City University of Hong Kong,Department of Computer Science

5. The Chinese University of Hong Kong,Department of Computer Science and Engineering

Funder

NSF China

Shenzhen Science and Technology Program

Publisher

IEEE

Reference30 articles.

1. PCC Vivace: Online-learning congestion control;dong;Proc of USENIX NSDI,2018

2. PCC: Rearchitecting congestion control for consistent high performance;dong;Proc of USENIX NSDI,2015

3. Dynamic TCP Initial Windows and Congestion Control Schemes Through Reinforcement Learning

4. On upper-confidence bound policies for non-stationary bandit problems;garivier;ArXiv Preprint,2008
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