Digital twin enabled asynchronous SplitFed learning in E-healthcare systems
V Stephanie, I Khalil… - IEEE Journal on Selected …, 2023 - ieeexplore.ieee.org
The advancement of Industrial Internet of Things (IIoT) technology has resulted in the fourth
industrial revolution, or Industry 4.0, enabling industries to enhance productivity. However …
industrial revolution, or Industry 4.0, enabling industries to enhance productivity. However …
On a novel high accuracy positioning with intelligent reflecting surface and unscented kalman filter for intelligent transportation systems in B5G
High accuracy and simultaneous positioning is an essential demand in future Intelligent
Transportation Systems (ITS), while the mobility and dynamics of vehicles place great …
Transportation Systems (ITS), while the mobility and dynamics of vehicles place great …
Federated learning over wireless networks: Challenges and solutions
M Beitollahi, N Lu - IEEE Internet of Things Journal, 2023 - ieeexplore.ieee.org
Motivated by ever-increasing computational resources at edge devices and increasing
privacy concerns, a new machine learning (ML) framework called federated learning (FL) …
privacy concerns, a new machine learning (ML) framework called federated learning (FL) …
A Spatiotemporal Backdoor Attack Against Behavior-Oriented Decision Makers In Metaverse: From Perspective of Autonomous Driving
Behavior-oriented decision-makers are critical components in generating intelligent
decisions for user virtual interactions in metaverse. In this work, we study the efficiency and …
decisions for user virtual interactions in metaverse. In this work, we study the efficiency and …
Federated Distillation: A Survey
Federated Learning (FL) seeks to train a model collaboratively without sharing private
training data from individual clients. Despite its promise, FL encounters challenges such as …
training data from individual clients. Despite its promise, FL encounters challenges such as …
Effectively heterogeneous federated learning: A pairing and split learning based approach
Federated Learning (FL) is a promising paradigm widely used in privacy-preserving
machine learning. It enables distributed devices to collaboratively train a model while …
machine learning. It enables distributed devices to collaboratively train a model while …
Optimized Task Scheduling and Virtual Object Management Based on Digital Twin for Distributed Edge Computing Networks
In this paper, we address the challenge of limited resources in Internet of Things (IoT)
devices by proposing a solution based on digital twin in distributed edge computing …
devices by proposing a solution based on digital twin in distributed edge computing …
Imperfect Digital Twin Assisted Low Cost Reinforcement Training for Multi-UAV Networks
Deep Reinforcement Learning (DRL) is widely used to optimize the performance of multi-
UAV networks. However, the training of DRL relies on the frequent interactions between the …
UAV networks. However, the training of DRL relies on the frequent interactions between the …