Federated learning-empowered mobile network management for 5G and beyond networks: From access to core
The fifth generation (5G) and beyond wireless networks are envisioned to provide an
integrated communication and computing platform that will enable multipurpose and …
integrated communication and computing platform that will enable multipurpose and …
A comprehensive survey of federated transfer learning: challenges, methods and applications
Federated learning (FL) is a novel distributed machine learning paradigm that enables
participants to collaboratively train a centralized model with privacy preservation by …
participants to collaboratively train a centralized model with privacy preservation by …
Characterizing and modeling mobile networks user traffic at millisecond level
The availability of datasets has been instrumental to drive advances in several disciplines
like computer vision, image processing, and natural language processing. However, in the …
like computer vision, image processing, and natural language processing. However, in the …
Reduction in data imbalance for client-side training in federated learning for the prediction of stock market prices
The approach of federated learning (FL) addresses significant challenges, including access
rights, privacy, security, and the availability of diverse data. However, edge devices produce …
rights, privacy, security, and the availability of diverse data. However, edge devices produce …
Federated learning: challenges, SoTA, performance improvements and application domains
I Schoinas, A Triantafyllou, D Ioannidis… - IEEE Open Journal …, 2024 - ieeexplore.ieee.org
Federated Learning has emerged as a revolutionary technology in Machine Learning (ML),
enabling collaborative training of models in a distributed environment while ensuring privacy …
enabling collaborative training of models in a distributed environment while ensuring privacy …
Deep Learning on Network Traffic Prediction: Recent Advances, Analysis, and Future Directions
From the perspective of telecommunications, next-generation networks or beyond 5G will
inevitably face the challenge of a growing number of users and devices. Such growth results …
inevitably face the challenge of a growing number of users and devices. Such growth results …
QoE-Aware Bandwidth Resource Allocation Strategy for Ultra High-Definition Video Services in B5G: A Game Theoretic Approach
Z Wang, X Liu, H Gu, S Mao… - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
With Ultra High-Definition video services developing in B5G networks, such as an Ultra High-
Definition video surveillance system with a resolution of 7680x4320p that generates video …
Definition video surveillance system with a resolution of 7680x4320p that generates video …
Enhancing Vehicular Networks With Hierarchical O-RAN Slicing and Federated DRL
With 5G technology evolving, Open Radio Access Network (O-RAN) solutions are becoming
crucial, especially for handling the diverse Quality of Service (QoS) needs in vehicular …
crucial, especially for handling the diverse Quality of Service (QoS) needs in vehicular …
Mobile network traffic analysis based on probability-informed machine learning approach
A Gorshenin, A Kozlovskaya, S Gorbunov… - Computer Networks, 2024 - Elsevier
The paper proposes an approach to the joint use of statistical and machine learning (ML)
models to solve the problems of the precise reconstruction of historical events, real-time …
models to solve the problems of the precise reconstruction of historical events, real-time …
Advancing Security and Efficiency in Federated Learning Service Aggregation for Wireless Networks
Z Abou El Houda, D Nabousli… - 2023 IEEE 34th Annual …, 2023 - ieeexplore.ieee.org
Federated Learning (FL) is a distributed machine learning technique where multiple devices
can collaboratively train a model without sharing their data. As a result, FL ensures distinct …
can collaboratively train a model without sharing their data. As a result, FL ensures distinct …