Security and privacy on 6g network edge: A survey
To meet the stringent service requirements of 6G applications such as immersive cloud
eXtended Reality (XR), holographic communication, and digital twin, there is no doubt that …
eXtended Reality (XR), holographic communication, and digital twin, there is no doubt that …
Performance-driven closed-loop optimization and control for smart manufacturing processes in the cloud-edge-device collaborative architecture: A review and new …
C Zhang, Y Wang, Z Zhao, X Chen, H Ye, S Liu… - Computers in …, 2024 - Elsevier
With the transformation and upgrading of the manufacturing industry, manufacturing systems
have become increasingly complex in terms of the structural functionality, process flows …
have become increasingly complex in terms of the structural functionality, process flows …
Privacy-aware multiagent deep reinforcement learning for task offloading in vanet
Offloading task to roadside units (RSUs) provides a promising solution for enhancing the
real-time data processing capacity and reducing energy consumption of vehicles in the …
real-time data processing capacity and reducing energy consumption of vehicles in the …
FedChain-Hunter: A reliable and privacy-preserving aggregation for federated threat hunting framework in SDN-based IIoT
In the development of the Industrial Internet of Things (IIoT), cyber threats and attacks have
become major issues and concerns in Industry 4.0 due to the negative impacts on the …
become major issues and concerns in Industry 4.0 due to the negative impacts on the …
TinyReptile: TinyML with federated meta-learning
Tiny machine learning (TinyML) is a rapidly growing field aiming to democratize machine
learning (ML) for resource-constrained microcontrollers (MCUs). Given the pervasiveness of …
learning (ML) for resource-constrained microcontrollers (MCUs). Given the pervasiveness of …