6 天前 - … To mitigate this, we employ a Federated Learning (FL) framework that shares model
… federated learning framework combining Graph Neural Networks (GNN), named Federated …

6 天前 - … to reduce communication overhead between multiple agents, and federated learning
(FL) … MEC system significantly while satisfying system resource and task delay constraints. …

11 天前 - … Finally, federated learning is introduced in the training process to reduce the
impact of non-IID data while protecting privacy. Simulation results show that the proposed …

19 天前 - … is based on 6G wireless communication network in smart healthcare system …
learning coyote foraging optimizer. Then the network CPS analysis is carried out using federated …

20 天前 - … such as edge computing and federated learning named … The authenticated nodes
are allowed to form the network, … scheduling) based on federated learning. By Performing …

30 天前 - … federated learning (DFL), every edge node promptly exchanges its model with a
neighbouring edge … Within this conceptual framework, the edge nodes directly communicate …

33 天前 - … : communication efficiency, communication environment, and … efficient communication
strategies for federated learning … of adverse effects on communication environments. We …

36 天前 - … communication period for balancing communication and … the effectiveness of
federated learning with a constant … period of the federated learning framework to achieve fast …

39 天前 - … Federated learning (FL) is an alternative solution to overcome … edge networks,
detailing its design, implementation, and evaluation, which substantially reduces communication …

50 天前 - … New cutting-edge technologies (cloud-fog-edge computing, blockchain, quantum
… , federated learning (FL), Internet of Things [IoT], machine learning (ML), deep learning (DL), …