An End-to-end Flow Control Method Based on DQN

被引：0
|
作者：
Gao, Guichao [1 ]
Jin, Rong [1 ]
机构：
[1] Zhejiang Gongshang Univ, Sch Informat & Elect Engn, Sussex Artificial Intelligence Inst, Hangzhou, Peoples R China
来源：
2022 INTERNATIONAL CONFERENCE ON BIG DATA, INFORMATION AND COMPUTER NETWORK (BDICN 2022) | 2022年
关键词：
flow control; SDN; DQN;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
We propose an end-to-end flow control method based on DQN (Deep-Q-Network). The flow control method is intelligent and flow-based, it is suitable for those DCNs (Data Center Network) based on SDN (Software Define Network) architecture. The system architecture is analyzed and an improved DQN algorithm is proposed. The training results show that the method has good convergence speed and convergence effect. The final test shows that the DQN-based end-to-end flow control method can effectively achieve DCN flow control by allocating the flow rates globally, and can improve the link utilization rate of the entire network as much as possible.
引用
收藏
页码：504 / 507
页数：4
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