A 3-CS Distributed Federated Transfer Learning Framework for Intelligent Edge Optical Networks

被引:2
|
作者
Yang, Hui [1 ]
Yao, Qiuyan [1 ]
Bao, Bowen [1 ]
Li, Chao [1 ]
Wang, Danshi [1 ]
Zhang, Jie [1 ]
Cheriet, Mohamed [2 ]
机构
[1] Beijing Univ Posts & Telecommun, State Key Lab Informat Photon & Opt Commun, Beijing, Peoples R China
[2] Univ Quebec, Dept Syst Engn, ETS, Montreal, PQ, Canada
基金
北京市自然科学基金;
关键词
edge optical network; distributed framework; artificial intelligence; federated transfer learning; cross-scene; cross-spectrum; cross-service; OPTIMIZATION; CORE;
D O I
10.3389/frcmn.2021.700912
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
With the rapid development of optical network and edge computing, the operation efficiency of the edge optical network has become more and more important, requiring an intelligent approach to enhance the network performance. To enhance the intelligence of the edge optical network, this article firstly provides the demand for the development of edge optical networks. Then, a cross-scene, cross-spectrum, and cross-service (3-CS) architecture for edge optical networks is presented. Finally, a federated transfer learning (FTL) framework, realizing a distributed intelligence edge optical network, is proposed. The usability of the proposed framework is verified by simulation.
引用
收藏
页数:6
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