Jan 29, 2021 · In Federated Learning (FL), a global statistical model is developed by encouraging mobile users to perform the model training on their local ...
Jan 11, 2021 · In this regard, Multi-access Edge Computing (MEC)-enabled FL addresses the tradeoff between the model performance and the energy consumption of ...
In Federated Learning (FL), a global statistical model is developed by encouraging mobile users to perform the model training on their local data and ...
PDF | In Federated Learning (FL), a global statistical model is developed by encouraging mobile users to perform the model training on their local data.
In this paper, we propose an Energy- aware Multi-Criteria Federated Learning (EaMC-FL) model for edge computing. The proposed model enables to collaboratively.
Energy-aware Resource Management for Federated Learning in Multi-access Edge Computing Systems. Journal: IEEE Access. Vol(Issue): Vol. 9. Page: pp. 34938-34950.
Multi-access edge computing (MAEC)-enabled FL eliminates the trade-off between the model performance and the energy use of mobile devices by allowing users to ...
In this paper, we describe the recent work on resource management at the edge and explore the challenges and future directions to allow the execution of ...
Jun 24, 2024 · This study proposes a novel energy-aware edge intelligence framework named FSLEdge, based on edge computing, to realize deep learning training in a distributed ...
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What is the difference between federated learning and edge computing?
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The recent work on resource management at the edge is described, and some of the problems of this management, such as discovery of resources, deployment, ...