Node-Oriented Traffic Prediction and Scheduling Based on Graph Convolutional Network in Metro Optical Networks

被引：0
|
作者：
Bao, Bowen [1 ]
Yang, Hui [1 ]
Wan, Yu [1 ]
Yao, Qiuyan [1 ]
Yu, Ao [1 ]
Zhang, Jie [1 ]
Chatterjee, Bijoy Chand [2 ]
Oki, Eiji [3 ]
机构：
[1] Beijing Univ Posts & Telecommun, State Key Lab Informat Photon & Opt Commun, Beijing, Peoples R China
[2] South Asian Univ, Dept Comp Sci, New Delhi, India
[3] Kyoto Univ, Grad Sch Informat, Kyoto, Japan
来源：
2021 OPTICAL FIBER COMMUNICATIONS CONFERENCE AND EXPOSITION (OFC) | 2021年
基金：
北京市自然科学基金;
关键词：
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
This paper proposes a node-oriented traffic prediction and scheduling in elastic metro optical networks by introducing the graph convolution network. Simulation results show the proposed scheme achieves efficient resource utilization with an accurate traffic prediction.
引用
收藏
页数：3
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