Experimental assessment of traffic prediction assisted data center network reconfiguration method

被引：0

作者：

Guo, Xiaotao ^{[1
]}

Xue, Xuwei ^{[1
]}

Yan, Fulong ^{[1
]}

Pan, Bitao ^{[1
]}

Exarchakos, Georgios ^{[1
]}

Calabretta, Nicola ^{[1
]}

机构：

[1] Eindhoven Univ Technol, Inst Photon Integrat, Eindhoven, Netherlands

来源：

2021 EUROPEAN CONFERENCE ON OPTICAL COMMUNICATION (ECOC) | 2021年

关键词：

D O I：

10.1109/ECOC52684.2021.9606079

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 experimentally demonstrate a traffic prediction assisted network reconfiguration method (TPANR) for data center networks based on deep reinforcement learning (DRL). Traffic prediction model performs the lowest MSE of 2.64E-4. Exploiting one-step ahead traffic prediction and DRL-based automatic network reconfiguration, TPANR achieves 17.3% latency improvement.

引用

页数：4

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