Auter: Automatically Tuning Multi-layer Network Buffers in Long-Distance Shadowsocks Networks-Reference-Cited by-同舟云学术

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Auter: Automatically Tuning Multi-layer Network Buffers in Long-Distance Shadowsocks Networks

Published:2022-05-02 Issue: Volume: Page:
ISSN:
Container-title:IEEE INFOCOM 2022 - IEEE Conference on Computer Communications
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Author:

He Xu¹,Cao Jiahao²,Wang Shu¹,Sun Kun¹,Xu Lisong³,Li Qi⁴

Affiliation:

1. George Mason University,Center for Secure Information Systems,VA,USA

2. Tsinghua University,Department of Computer Science and Technology,Beijing,China

3. University of Nebraska-Lincoln,School of Computing,NE,USA

4. Tsinghua University,Institute for Network Sciences and Cyberspace,Beijing,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9796607/9796652/09796882.pdf?arnumber=9796882

Reference39 articles.

1. Two-dimensional anti-jamming communication based on deep reinforcement learning

2. Robust Deep Reinforcement Learning for Security and Safety in Autonomous Vehicle Systems

3. Project ”tuned": Daemon for monitoring and adaptive tuning of system devices,2020

4. Reducing Web Latency Through Dynamically Setting TCP Initial Window with Reinforcement Learning

5. Expanding across time to deliver bandwidth efficiency and low latency;mellette;USENIX Symposium on Networked Systems Design and Implementation (NSDI),2020

Cited by 1 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. Accelerating Data Delivery of Latency-Sensitive Applications in Container Overlay Network;IEEE Transactions on Parallel and Distributed Systems;2023-12

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