Toward enhanced reinforcement learning-based resource management via digital twin: Opportunities, applications, and challenges
This article presents a digital twin (DT)-enhanced reinforcement learning (RL) framework
aimed at optimizing performance and reliability in network resource management, since the …
aimed at optimizing performance and reliability in network resource management, since the …
A Bayesian framework for digital twin-based control, monitoring, and data collection in wireless systems
Commonly adopted in the manufacturing and aerospace sectors, digital twin (DT) platforms
are increasingly seen as a promising paradigm to control, monitor, and analyze software …
are increasingly seen as a promising paradigm to control, monitor, and analyze software …
Digital twin driven service self-healing with graph neural networks in 6g edge networks
6G edge networks strive to offer ubiquitous intelligent services, requiring a greater emphasis
on network stability and reliability. However, current networks present a low automation …
on network stability and reliability. However, current networks present a low automation …
Digital twin-assisted knowledge distillation framework for heterogeneous federated learning
In this paper, to deal with the heterogeneity in federated learning (FL) systems, a knowledge
distillation (KD) driven training framework for FL is proposed, where each user can select its …
distillation (KD) driven training framework for FL is proposed, where each user can select its …
Adaptive task scheduling in digital twin empowered cloud-native vehicular networks
Intelligent driving has advanced significantly in recent decades, paving the path for the
transportation of the future. Digital twin (DT) technology, which can bridge the physical and …
transportation of the future. Digital twin (DT) technology, which can bridge the physical and …
Cost-aware workflow offloading in edge-cloud computing using a genetic algorithm
The edge-cloud computing continuum effectively uses fog and cloud servers to meet the
quality of service (QoS) requirements of tasks when edge devices cannot meet those …
quality of service (QoS) requirements of tasks when edge devices cannot meet those …
Decision support for personalized therapy in implantable medical devices: A digital twin approach
H Yang, Z Jiang - Expert Systems with Applications, 2024 - Elsevier
Abstract Implantable Medical Devices (IMDs) offer timely therapeutic interventions for life-
threatening conditions without disrupting patients' daily activities. Given the substantial …
threatening conditions without disrupting patients' daily activities. Given the substantial …
Scalable resource management for dynamic mec: An unsupervised link-output graph neural network approach
Deep learning has been successfully adopted in mobile edge computing (MEC) to optimize
task offloading and resource allocation. However, the dynamics of edge networks raise two …
task offloading and resource allocation. However, the dynamics of edge networks raise two …
Digital twin-based multiple access optimization and monitoring via model-driven bayesian learning
Commonly adopted in the manufacturing and aerospace sectors, digital twin (DT) platforms
are increasingly seen as a promising paradigm to control and monitor software …
are increasingly seen as a promising paradigm to control and monitor software …
A Digital Twins-Assisted Multi-Autonomous Vehicle Distributed Collaborative Path Planning Algorithm With Fidelity Guarantee
L Tang, J Dai, Z Cheng, H Zhang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Autonomous driving is state-of-the-art technology in the field of Internet of Vehicles (IoVs),
considered a revolutionary solution to enhance driving safety and comfort. Collaborative …
considered a revolutionary solution to enhance driving safety and comfort. Collaborative …