FLight: A Lightweight Federated Learning Framework in Edge and Fog
Computing

FLight: A Lightweight Federated Learning Framework in Edge and Fog Computing

5 August 2023

Rajkumar Buyya

Papers citing "FLight: A Lightweight Federated Learning Framework in Edge and Fog Computing"

6 / 6 papers shown

Title
Edge-Cloud Collaborative Computing on Distributed Intelligence and Model Optimization: A Survey J. H. Liu Yao Du Kun Yang Yan Wang Xiping Hu Z. Wang Y. Liu Peng Sun Azzedine Boukerche Victor C.M. Leung 40 0 0 03 May 2025
A Distributed Deep Reinforcement Learning Technique for Application Placement in Edge and Fog Computing Environments M. Goudarzi M. Palaniswami Rajkumar Buyya OffRL 27 85 0 24 Oct 2021
Federated Dropout -- A Simple Approach for Enabling Federated Learning on Resource Constrained Devices Dingzhu Wen Ki-Jun Jeon Kaibin Huang FedML 68 90 0 30 Sep 2021
Asynchronous Federated Learning on Heterogeneous Devices: A Survey Chenhao Xu Youyang Qu Yong Xiang Longxiang Gao FedML 91 241 0 09 Sep 2021
Federated Learning: Opportunities and Challenges P. Mammen FedML 44 211 0 14 Jan 2021
Adaptive Federated Learning in Resource Constrained Edge Computing Systems Shiqiang Wang Tiffany Tuor Theodoros Salonidis K. Leung C. Makaya T. He Kevin S. Chan 144 1,685 0 14 Apr 2018