Federated Privacy-Preserving Strategy for Generalizing Soft-Failure Localization in Multi-Carrier Optical Networks
We propose a privacy-preserving strategy based on federated learning to localize soft failures in multi-carrier optical networks using a self-supervised approach on unlabeled data. Evaluations conducted on data from a testbed demonstrate the effectiveness of the proposed strategy.
Authors
- Masaki Shiraiwa
- Forough Shirin Abkenar (ORCID: https://orcid.org/0000-0003-0233-4306)
- Yoshinari Awaji
- Massimo Tornatore (ORCID: https://orcid.org/0000-0003-0740-1061)
- Venkata Virajit Garbhapu (ORCID: https://orcid.org/0009-0003-9507-7069)
- Yusuke Hirota (ORCID: https://orcid.org/0000-0002-4661-9584)
- Sifat Ferdousi (ORCID: https://orcid.org/0000-0002-9050-4274)
- Ramanuja Kalkunte
- Biswanath Mukherjee (ORCID: https://orcid.org/0000-0002-1483-1257)
- Sugang Xu (ORCID: https://orcid.org/0000-0002-0937-0097)
- Aryanaz Attarpour (ORCID: https://orcid.org/0009-0001-9181-3423)
Institutions
- Huawei Technologies (France) (FR)
- National Institute on Consumer Education (JP)
- University of California, Davis (US)
- Politecnico di Milano (IT)
Publication Details
- Published
- 2025-05-06
- DOI
- https://doi.org/10.23919/ondm65745.2025.11029227
- Primary Topic
- Optical Network Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00