US 12,309,038 B2
Network data analysis method and system based on federated learning
Soohwan Lee, Daejeon (KR)
Assigned to ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE, Daejeon (KR)
Filed by ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE, Daejeon (KR)
Filed on May 5, 2023, as Appl. No. 18/313,205.
Claims priority of application No. 10-2022-0056162 (KR), filed on May 6, 2022; application No. 10-2022-0062175 (KR), filed on May 20, 2022; application No. 10-2022-0146516 (KR), filed on Nov. 4, 2022; application No. 10-2023-0002928 (KR), filed on Jan. 9, 2023; and application No. 10-2023-0057978 (KR), filed on May 3, 2023.
Prior Publication US 2024/0080245 A1, Mar. 7, 2024
Int. Cl. H04L 41/14 (2022.01); H04L 41/16 (2022.01)
CPC H04L 41/145 (2013.01) [H04L 41/16 (2013.01)] 18 Claims
OG exemplary drawing
 
1. An operating method of a federation learning (FL) server, the method comprising:
performing an FL operation trigger in response to a request of a first network function (NF); and
in response to the FL operation trigger:
selecting a plurality of second NFs on an analytics identifier (ID);
requesting the plurality of second NFs for FL,
receiving one or more trained interim machine learning (ML) models from the plurality of second NFs,
aggregating the trained interim ML models from the plurality of second NFs to produce a trained ML model, and
providing the trained ML model to the first NF,
wherein the first NF is an FL consumer, and
wherein the plurality of second NFs includes an FL client and does not include the first NF.