A value-added IoT service for cellular networks using federated learning
The number of Internet-of-Things (IoT) devices is expected to reach 64 billion by 2025.
These IoT devices will mostly use cellular networks for transferring a huge amount of IoT …
These IoT devices will mostly use cellular networks for transferring a huge amount of IoT …
Optimizing resource-efficiency for federated edge intelligence in IoT networks
This paper studies an edge intelligence-based IoT network in which a set of edge servers
learn a shared model using federated learning (FL) based on the datasets uploaded from a …
learn a shared model using federated learning (FL) based on the datasets uploaded from a …
Federated learning based on CTC for heterogeneous internet of things
Federated learning (FL) is a machine learning technique that allows for on-site data
collection and processing without sacrificing data privacy and transmission. Heterogeneity is …
collection and processing without sacrificing data privacy and transmission. Heterogeneity is …
Energy-efficient federated learning with resource allocation for green IoT edge intelligence in B5G
An edge intelligence-aided Internet-of-Things (IoT) network has been proposed to
accelerate the response of IoT services by deploying edge intelligence near IoT devices …
accelerate the response of IoT services by deploying edge intelligence near IoT devices …
Combining federated learning and edge computing toward ubiquitous intelligence in 6G network: Challenges, recent advances, and future directions
Full leverage of the huge volume of data generated on a large number of user devices for
providing intelligent services in the 6G network calls for Ubiquitous Intelligence (UI). A key to …
providing intelligent services in the 6G network calls for Ubiquitous Intelligence (UI). A key to …
Realizing the heterogeneity: A self-organized federated learning framework for IoT
The ubiquity of devices in Internet of Things (IoT) has opened up a large source for IoT data.
Machine learning (ML) models with big IoT data is beneficial to our daily life in monitoring air …
Machine learning (ML) models with big IoT data is beneficial to our daily life in monitoring air …
Communication-efficient federated learning for wireless edge intelligence in IoT
The rapidly expanding number of Internet of Things (IoT) devices is generating huge
quantities of data, but public concern over data privacy means users are apprehensive to …
quantities of data, but public concern over data privacy means users are apprehensive to …
Optimizing federated learning in distributed industrial IoT: A multi-agent approach
In this paper, we aim to make the best joint decision of device selection and computing and
spectrum resource allocation for optimizing federated learning (FL) performance in …
spectrum resource allocation for optimizing federated learning (FL) performance in …
Federated learning over wireless IoT networks with optimized communication and resources
To leverage massive distributed data and computation resources, machine learning in the
network edge is considered to be a promising technique, especially for large-scale model …
network edge is considered to be a promising technique, especially for large-scale model …
Communication-efficient device scheduling via over-the-air computation for federated learning
Artificial intelligence (AI) is expected as a revo-lutionary technology to be widely used in
Internet-of-Things (IoT) networks for computationally intensive tasks. However, the traditional …
Internet-of-Things (IoT) networks for computationally intensive tasks. However, the traditional …
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