Asynchronous federated deep reinforcement learning-based URLLC-aware computation offloading in space-assisted vehicular networks

C Pan, Z Wang, H Liao, Z Zhou, X Wang… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Space-assisted vehicular networks (SAVN) provide seamless coverage and on-demand
data processing services for user vehicles (UVs). However, ultra-reliable and low-latency …

Optimal task offloading and resource allocation for C-NOMA heterogeneous air-ground integrated power Internet of Things networks

P Qin, Y Fu, X Zhao, K Wu, J Liu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
By combining information communication technology with power grid, the smart grid-
oriented Power Internet of Things (PIoT) has become a critical technology to guarantee the …

Cloud-edge-end collaboration in air–ground integrated power IoT: A semidistributed learning approach

H Liao, Z Jia, Z Zhou, Y Wang, H Zhang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The combination of air–ground integrated power Internet of Things (AGI-PIoT) and cloud-
edge-end collaboration enables flexible coverage and real-time data processing. However …

Multi-agent learning-based optimal task offloading and UAV trajectory planning for AGIN-power IoT

P Qin, Y Fu, Y Xie, K Wu, X Zhang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
UAV-based air-ground integrated computing networks (AGIN) have gained significant
traction in remote areas for the Power Internet of Things (PIoT). This paper considers an …

Approaches towards blockchain innovation: A survey and future directions

D Guru, S Perumal, V Varadarajan - Electronics, 2021 - mdpi.com
A blockchain is a decentralized peer to peer platform which provides security services based
on some key concepts, namely authentication, confidentiality, integrity and authorization. It is …

Exploring targeted and stealthy false data injection attacks via adversarial machine learning

J Tian, B Wang, J Li, Z Wang, B Ma… - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
State estimation methods used in cyber–physical systems (CPSs), such as smart grid, are
vulnerable to false data injection attacks (FDIAs). Although substantial deep learning …

Experience-driven attack design and federated-learning-based intrusion detection in industry 4.0

B Tahir, A Jolfaei, M Tariq - IEEE Transactions on Industrial …, 2021 - ieeexplore.ieee.org
The advent of Industry 4.0 facilitates the Int-ernet-of-Things-based-transactive energy system
(IoTES), which enables innovative services with numerous independent distributed systems …

Feddp: A privacy-protecting theft detection scheme in smart grids using federated learning

MM Ashraf, M Waqas, G Abbas, T Baker, ZH Abbas… - Energies, 2022 - mdpi.com
In smart grids (SGs), the systematic utilization of consumer energy data while maintaining its
privacy is of paramount importance. This research addresses this problem by energy theft …

Collaborative learning-based network resource scheduling and route management for multi-mode green iot

Z Zhou, X Chen, H Liao, Z Gan, F Xiao… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
The multi-mode green Internet of things (IoT) provides a communication support for social
assets of smart park connecting to power grid for low-carbon operation. Software defined …

Adaptive and dynamic security in AI-empowered 6G: From an energy efficiency perspective

S Shen, C Yu, K Zhang, J Ni, S Ci - IEEE Communications …, 2021 - ieeexplore.ieee.org
Emerging AI-empowered services and techniques, such as connected vehicle, intelligent
industry, and smart city, are forthcoming with the sixth generation (6G) cellular network to …