Sep 16, 2024 � User selection has became crucial for improving energy efficiency in communication of federated learning (FL) over wireless networks.
Federated Learning with CSMA Based User Selection for IoT ...
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Sep 1, 2024 � Such support is realized by enhancing existing functions such as Quality of Service (QoS) management, network information exposure to AI�...
Jul 7, 2023 � This study proposes a network intrinsic approach of distributed user selection that leverages the radio resource competition mechanism in random access.
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Federated learning over a wireless network: Distributed user selection ... 2023. Federated Learning with CSMA Based User Selection for IoT Applications.
In this article, we investigate the performance of FL on an application that might be used to improve a remote healthcare system over ad hoc networks which�...
The main goal of this research is to present a literature review of federated reinforcement learning (FRL) applications in IoT from multiple perspectives.
The proposed framework aims to accommodate the ad-hoc nature of IoT devices, and at the same time avoiding low quality or even malicious data from its�...
Missing: CSMA | Show results with:CSMA
Dec 6, 2023 � Federated learning (FL) has made a decentralized, cooperative AI system that can be used by many IoT apps that use AI. It is possible because it�...
Missing: CSMA | Show results with:CSMA
This study presents a comprehensive systematic literature review (SLR) that focuses on the challenges of client selection (CS) in the context of federated�...
Missing: CSMA | Show results with:CSMA
Particularly, we explore and analyze the potential of FL for enabling a wide range of IoT services, including IoT data sharing, data offloading and caching,�...
Missing: CSMA | Show results with:CSMA