Traffic Prediction in Satellite Optical Networks Based on Asynchronous Federated Learning
This paper presents a traffic prediction method for satellite optical networks using asynchronous federated learning, enhancing model convergence, reducing communication burden, and addressing traffic distribution and overload challenges while ensuring privacy.
Authors
- Shangshang Qin (ORCID: https://orcid.org/0000-0002-6017-6548)
- Xueqiang Zhao (ORCID: https://orcid.org/0000-0002-4956-6932)
- Longchao Wei
- Pengyu Wang (ORCID: https://orcid.org/0000-0003-4581-9004)
- Yajun Li (ORCID: https://orcid.org/0000-0002-6152-0355)
- Zihao Qin
- Ruijie Zhu (ORCID: https://orcid.org/0000-0001-9316-7245)
- Haicheng Li
- Xiaoke Sun
Institutions
- China Electronics Technology Group Corporation (CN)
- Zhengzhou University (CN)
Publication Details
- Published
- 2024-11-02
- DOI
- https://doi.org/10.1109/acp/ipoc63121.2024.10809505
- Primary Topic
- Advanced Optical Network Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China