Joint optimization risk factor and energy consumption in IoT networks with TinyML-enabled internet of UAVs

R Liu, M **e, A Liu, H Song - IEEE Internet of Things Journal, 2024‏ - ieeexplore.ieee.org
The high mobility of Internet unmanned aerial vehicles (IUAVs) has attracted attention in the
field of data collection. With the rapid development of the Internet of Things (IoT), more and …

Periodic collaboration and real-time dispatch using an actor–critic framework for uav movement in mobile edge computing

H Zeng, Z Zhu, Y Wang, Z **ang… - IEEE Internet of Things …, 2024‏ - ieeexplore.ieee.org
The increasing need for communication capabilities in mobile devices has led to the
recognition of mobile edge computing (MEC) as a critical solution for addressing …

Wireless powered metaverse: Joint task scheduling and trajectory design for multi-devices and multi-UAVs

X Wang, J Li, Z Ning, Q Song, L Guo… - IEEE Journal on …, 2023‏ - ieeexplore.ieee.org
To support the running of human-centric metaverse applications on mobile devices,
Unmanned Aerial Vehicle (UAV)-assisted Wireless Powered Mobile Edge Computing …

Multiagent Reinforcement Learning: Methods, Trustworthiness, Applications in Intelligent Vehicles, and Challenges

Z Zhou, G Liu, Y Tang - IEEE Transactions on Intelligent …, 2024‏ - ieeexplore.ieee.org
Multiagent Reinforcement Learning (MARL) plays a pivotal role in intelligent vehicle
systems, offering solutions for complex decision-making, coordination, and adaptive …

A Survey on Security of UAV Swarm Networks: Attacks and Countermeasures

X Wang, Z Zhao, L Yi, Z Ning, L Guo, FR Yu… - ACM Computing …, 2024‏ - dl.acm.org
The increasing popularity of Unmanned Aerial Vehicle (UAV) swarms is attributed to their
ability to generate substantial returns for various industries at a low cost. Additionally, in the …

Profit-aware cooperative offloading in uav-enabled mec systems using lightweight deep reinforcement learning

Z Chen, J Zhang, X Zheng, G Min, J Li… - IEEE Internet of things …, 2023‏ - ieeexplore.ieee.org
In mobile edge computing (MEC) systems, unmanned aerial vehicles (UAVs) facilitate edge
service providers (ESPs) offering flexible resource provisioning with broader communication …

Energy efficiency optimization of IRS and UAV-assisted wireless powered edge networks

X Wang, J Li, J Wu, L Guo, Z Ning - IEEE Journal of Selected …, 2024‏ - ieeexplore.ieee.org
With the surge in the number of Internet of Things (IoT) devices and latency-sensitive
services such as smart cities and smart factories, Next Generation Multiple Access (NGMA) …

Energy consumption optimization of UAV-assisted traffic monitoring scheme with tiny reinforcement learning

X Kong, C Ni, G Duan, G Shen… - IEEE Internet of Things …, 2024‏ - ieeexplore.ieee.org
Unmanned aerial vehicles (UAVs) equipped with high-definition cameras have the
capability to capture comprehensive and multiangled images of road conditions, facilitating …

Bias-compensation augmentation learning for semantic segmentation in UAV networks

T Yu, H Yang, J Nie, Q Yao, W Liu… - IEEE Internet of …, 2024‏ - ieeexplore.ieee.org
In the realm of emergency disaster relief, it is paramount to attain a thorough comprehension
of the semantic information associated with the local disaster scene for strategic rescue path …

A trust and privacy-preserving intelligent big data collection scheme in mobile edge-cloud crowdsourcing

Z Sun, A Liu, NN **ong, Q He, S Zhang - Future Generation Computer …, 2024‏ - Elsevier
As one of important Edge-Cloud solutions, mobile crowd sensing (MCS) platform resides in
the cloud, and recruits massive workers in the edge network to sense data, so big data can …