Towards energy-efficient federated edge intelligence for iot networks
Federated edge intelligence (FEI) is an emerging framework that implements federated
learning (FL)-based learning solutions in an edge networking and computing system. It has …
learning (FL)-based learning solutions in an edge networking and computing system. It has …
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 …
Fine-grained data selection for improved energy efficiency of federated edge learning
In Federated edge learning (FEEL), energy-constrained devices at the network edge
consume significant energy when training and uploading their local machine learning …
consume significant energy when training and uploading their local machine learning …
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 …
Energy-efficient multiprocessor-based computation and communication resource allocation in two-tier federated learning networks
In conventional federated learning (FL), multiple edge devices holding local data jointly train
a machine learning model by communicating learning updates with a centralized aggregator …
a machine learning model by communicating learning updates with a centralized aggregator …
Energy-aware edge federated learning for enhanced reliability and sustainability
M Mendula, P Bellavista - 2022 IEEE/ACM 7th Symposium on …, 2022 - ieeexplore.ieee.org
Federated Learning (FL) has emerged as a value added proposition for use in edge-based
infrastructures, distributing the training process among collaborative workers without …
infrastructures, distributing the training process among collaborative workers without …
Spectrum and computing resource management for federated learning in distributed industrial IoT
Federated learning (FL) is a distributed paradigm to support deep neural network (DNN)
training while preserving the data owners' privacy. In this paper, we investigate the resource …
training while preserving the data owners' privacy. In this paper, we investigate the resource …
Joint device selection and bandwidth allocation for cost-efficient federated learning in industrial internet of things
Along with the deployment of Industrial Internet of Things (IIoT), massive amounts of
industrial data have been generated at the network edge, driving the evolution of edge …
industrial data have been generated at the network edge, driving the evolution of edge …
Energy-aware, device-to-device assisted federated learning in edge computing
The surging of deep learning brings new vigor and vitality to shape the prospect of intelligent
Internet of Things (IoT), and the rise of edge intelligence enables provisioning real-time …
Internet of Things (IoT), and the rise of edge intelligence enables provisioning real-time …
[HTML][HTML] HED-FL: A hierarchical, energy efficient, and dynamic approach for edge Federated Learning
The increasing data produced by IoT devices and the need to harness intelligence in our
environments impose the shift of computing and intelligence at the edge, leading to a novel …
environments impose the shift of computing and intelligence at the edge, leading to a novel …