Q-Learning Based Adaptive Flow Control

With the rapid development of the internet and the expansion of its application scale, the volatility and complexity of network flow in highly concurrent environments have become increasingly prominent. Traditional static control strategies have been difficult to meet the actual needs. Traditional f...

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Bibliographic Details

Published in:	2023 5th International Conference on Data-driven Optimization of Complex Systems (DOCS) pp. 1 - 6
Main Authors:	Zhang, Xiaoping, Wang, Yunlan, Zhao, Tianhai, Hu, Shuai, Zhang, Hui
Format:	Conference Proceeding
Language:	English
Published:	IEEE 22.09.2023
Subjects:	Adaptation models adaptive flow control network flow Concurrent computing high concurrency Machine learning algorithms Q-learning sentinel Stability analysis Throughput Training
Online Access:	Get full text
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