Optimizing intelligent edge computing resource scheduling based on federated learning
This study proposes a novel federated learning framework for optimizing intelligent edge
computing resource scheduling. The framework addresses the challenges of device …
computing resource scheduling. The framework addresses the challenges of device …
A Comprehensive Survey on Joint Resource Allocation Strategies in Federated Edge Learning
Federated Edge Learning (FEL), an emerging distributed Machine Learning (ML) paradigm,
enables model training in a distributed environment while ensuring user privacy by using …
enables model training in a distributed environment while ensuring user privacy by using …
Trustworthy Federated Learning: A Comprehensive Review, Architecture, Key Challenges, and Future Research Prospects
Federated Learning (FL) emerged as a significant advancement in the field of Artificial
Intelligence (AI), enabling collaborative model training across distributed devices while …
Intelligence (AI), enabling collaborative model training across distributed devices while …
A trust and data quality-based dynamic node selection and aggregation optimization in federated learning
Federated learning (FL) is a cutting-edge approach to machine learning where multiple
clients (or nodes) collaboratively train a model while keeping their data localized. This …
clients (or nodes) collaboratively train a model while keeping their data localized. This …
A Trustworthy Federated Learning Model: Client Selection for IoT Edge Networks
M Telçeken, E Bozkaya-Aras - 2024 Innovations in Intelligent …, 2024 - ieeexplore.ieee.org
The interaction between the Internet of Things (IoT) and edge computing plays a critical role
in processing and analyzing massive amounts of data. However, due to the malicious …
in processing and analyzing massive amounts of data. However, due to the malicious …