A survey of intelligent network slicing management for industrial IoT: Integrated approaches for smart transportation, smart energy, and smart factory
Network slicing has been widely agreed as a promising technique to accommodate diverse
services for the Industrial Internet of Things (IIoT). Smart transportation, smart energy, and …
services for the Industrial Internet of Things (IIoT). Smart transportation, smart energy, and …
Deep reinforcement learning in smart manufacturing: A review and prospects
To facilitate the personalized smart manufacturing paradigm with cognitive automation
capabilities, Deep Reinforcement Learning (DRL) has attracted ever-increasing attention by …
capabilities, Deep Reinforcement Learning (DRL) has attracted ever-increasing attention by …
Artificial intelligence for the metaverse: A survey
Along with the massive growth of the Internet from the 1990s until now, various innovative
technologies have been created to bring users breathtaking experiences with more virtual …
technologies have been created to bring users breathtaking experiences with more virtual …
FedCPF: An efficient-communication federated learning approach for vehicular edge computing in 6G communication networks
The sixth-generation network (6G) is expected to achieve a fully connected world, which
makes full use of a large amount of sensitive data. Federated Learning (FL) is an emerging …
makes full use of a large amount of sensitive data. Federated Learning (FL) is an emerging …
Blockchain-empowered space-air-ground integrated networks: Opportunities, challenges, and solutions
The terrestrial networks face the challenges of severe cost inefficiency and low feasibility to
provide seamless services anytime and anywhere, especially in the extreme or hotspot …
provide seamless services anytime and anywhere, especially in the extreme or hotspot …
Balancing QoS and security in the edge: Existing practices, challenges, and 6G opportunities with machine learning
While the emerging 6G networks are anticipated to meet the high-end service quality
demands of the mobile edge users in terms of data rate and delay satisfaction, new attack …
demands of the mobile edge users in terms of data rate and delay satisfaction, new attack …
Uav-assisted task offloading for iot in smart buildings and environment via deep reinforcement learning
J Xu, D Li, W Gu, Y Chen - Building and Environment, 2022 - Elsevier
With the rapid development of Internet of Things (IoT) techniques, IoT devices with sensors
have been widely deployed and used in smart buildings and environment, and the …
have been widely deployed and used in smart buildings and environment, and the …
Cost minimization-oriented computation offloading and service caching in mobile cloud-edge computing: An A3C-based approach
This paper considers computation offloading and service caching in a three-tier mobile
cloud-edge computing structure, in which Mobile Users (MUs) have subscribed to the Cloud …
cloud-edge computing structure, in which Mobile Users (MUs) have subscribed to the Cloud …
IoT data analytics in dynamic environments: From an automated machine learning perspective
With the wide spread of sensors and smart devices in recent years, the data generation
speed of the Internet of Things (IoT) systems has increased dramatically. In IoT systems …
speed of the Internet of Things (IoT) systems has increased dramatically. In IoT systems …
Deep reinforcement learning based energy management strategies for electrified vehicles: Recent advances and perspectives
H He, X Meng, Y Wang, A Khajepour, X An… - … and Sustainable Energy …, 2024 - Elsevier
Electrified vehicles provide an effective solution to address the unfavorable impacts of fossil
fuel use in the transportation sector. Energy management strategy (EMS) is the core …
fuel use in the transportation sector. Energy management strategy (EMS) is the core …