Federated TSK Models for Predicting Quality of Experience in B5G/6G Networks

Jose Luis Corcuera Barcena, Pietro Ducange, Francesco Marcelloni, Alessandro Renda, Fabrizio Ruffini, Alessio Schiavo

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

1 Cita (Scopus)

Resumen

Real-time applications based on streaming data collected from remote devices, such as smartphones and vehicles, are commonly developed using Artificial Intelligence (AI). Such applications must fulfill different requirements: on one hand, they must ensure good performance and must deliver results in a timely manner; on the other hand, with the objective of being compliant with the AI-specific regulations, they shall preserve data privacy and guarantee a certain level of explainability. In this paper, we describe an AI-based application to predict the Quality of Experience (QoE) for videos acquired by moving vehicles from Beyond 5G and 6G (B5G/6G) network data. To this aim, we exploit a Takagi-Sugeno-Kang (TSK) fuzzy model learned by employing a federated approach, thus meeting, simultaneously, the requests for explainability and data privacy preservation. A thorough experimental analysis, involving also the comparison with an opaque baseline (i.e., a neural network model), is presented and shows that the TSK model can be regarded as a viable solution which guarantees on the one side an optimal trade-off between interpretability and accuracy, and on the other side preserves the data privacy.

Idioma originalInglés
Título de la publicación alojada2023 IEEE International Conference on Fuzzy Systems, FUZZ 2023
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9798350332285
DOI
EstadoPublicada - 2023
Publicado de forma externa
Evento2023 IEEE International Conference on Fuzzy Systems, FUZZ 2023 - Incheon, República de Corea
Duración: 13 ago. 202317 ago. 2023

Serie de la publicación

NombreIEEE International Conference on Fuzzy Systems
ISSN (versión impresa)1098-7584

Conferencia

Conferencia2023 IEEE International Conference on Fuzzy Systems, FUZZ 2023
País/TerritorioRepública de Corea
CiudadIncheon
Período13/08/2317/08/23

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