Topology-aware federated learning in edge computing: A comprehensive survey
The ultra-low latency requirements of 5G/6G applications and privacy constraints call for
distributed machine learning systems to be deployed at the edge. With its simple yet …
distributed machine learning systems to be deployed at the edge. With its simple yet …
DRL-based joint resource allocation and device orchestration for hierarchical federated learning in NOMA-enabled industrial IoT
Federated learning (FL) provides a new paradigm for protecting data privacy in Industrial
Internet of Things (IIoT). To reduce network burden and latency brought by FL with a …
Internet of Things (IIoT). To reduce network burden and latency brought by FL with a …
Distance-aware hierarchical federated learning in blockchain-enabled edge computing network
Federated learning (FL) has been proposed as an emerging paradigm to perform privacy-
preserving distributed machine learning in the Internet of Things (IoT). However, the …
preserving distributed machine learning in the Internet of Things (IoT). However, the …
Energy minimization for UAV swarm-enabled wireless inland ship MEC network with time windows
Y Liao, X Chen, S Xia, Q Ai, Q Liu - IEEE Transactions on Green …, 2022 - ieeexplore.ieee.org
This paper establishes a new unmanned aerial vehicle (UAV) swarm-enabled wireless
inland ship mobile edge computing (MEC) network with time windows, where UAVs are …
inland ship mobile edge computing (MEC) network with time windows, where UAVs are …
Secure video offloading in MEC-enabled IIoT networks: A multi-cell federated deep reinforcement learning approach
Wireless video offloading in mobile-edge-computing (MEC)-enabled Industrial Internet of
Things imposes a risk of exposing users' private data to eavesdroppers. It is difficult for …
Things imposes a risk of exposing users' private data to eavesdroppers. It is difficult for …
Wireless federated learning with hybrid local and centralized training: A latency minimization design
Wireless federated learning (FL) is a collaborative machine learning (ML) framework in
which wireless client-devices independently train their ML models and send the locally …
which wireless client-devices independently train their ML models and send the locally …
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 …
UAV Swarm-Assisted Two-Tier Hierarchical Federated Learning
Federated Learning (FL) enables the distributed machine learning (ML) without violating the
privacy of local users. In the scenario wireless FL, it is challenging for some local clients to …
privacy of local users. In the scenario wireless FL, it is challenging for some local clients to …
Joint Resource Allocation and Learning Optimization for UAV-Assisted Federated Learning
C Liu, Q Zhu - Applied Sciences, 2023 - mdpi.com
Aiming at the unmanned aerial vehicle (UAV)-assisted federated learning wireless-network
scenario, and considering the influence of the UAV altitude on the coverage area, we …
scenario, and considering the influence of the UAV altitude on the coverage area, we …
Submodel partitioning in hierarchical federated learning: Algorithm design and convergence analysis
Hierarchical federated learning (HFL) has demonstrated promising scalability advantages
over the traditional" star-topology" architecture-based federated learning (FL). However, HFL …
over the traditional" star-topology" architecture-based federated learning (FL). However, HFL …