A comprehensive survey on aerial mobile edge computing: Challenges, state-of-the-art, and future directions

Z Song, X Qin, Y Hao, T Hou, J Wang, X Sun - Computer Communications, 2022 - Elsevier
Driven by the visions of Internet of Things (IoT), there is an ever-increasing demand for
computation resources of IoT users to support diverse applications. Mobile edge computing …

[HTML][HTML] Complementarity, interoperability, and level of integration of humanitarian drones with emerging digital technologies: A state-of-the-art systematic literature …

E Aretoulaki, ST Ponis, G Plakas - Drones, 2023 - mdpi.com
The adoption of drones and other emerging digital technologies (DTs) has proven essential
in revolutionizing humanitarian logistics as standalone solutions. However, the …

Achieve load balancing in multi-UAV edge computing IoT networks: A dynamic entry and exit mechanism

H Guo, X Zhou, Y Wang, J Liu - IEEE Internet of Things Journal, 2022 - ieeexplore.ieee.org
With the gradual commercialization of 5G, especially the widespread application of artificial
intelligence (AI) technology, the Internet of Things (IoT) continues to expand and has …

A survey on deep reinforcement learning-driven task offloading in aerial access networks

TH Nguyen, L Park - 2022 13th International Conference on …, 2022 - ieeexplore.ieee.org
Internet of Things computation offloading is a challenging problem, particularly in distant
places where mobile edge computing (MEC) or cloud infrastructure is absent. Fortunately …

Joint offloading and resource allocation using deep reinforcement learning in mobile edge computing

X Zhang, X Zhang, W Yang - IEEE Transactions on Network …, 2022 - ieeexplore.ieee.org
Mobile edge computation offloading (MECO) has recently emerged as a promising method
to support computation-intensive and latency-sensitive applications, significantly saving the …

[HTML][HTML] A prescriptive Dirichlet power allocation policy with deep reinforcement learning

Y Tian, M Han, C Kulkarni, O Fink - Reliability Engineering & System Safety, 2022 - Elsevier
Prescribing optimal operation based on the condition of the system, and thereby potentially
prolonging its remaining useful lifetime, has tremendous potential in terms of actively …

QoE-Driven Video Transmission: Energy-Efficient Multi-UAV Network Optimization

K Wu, X Cao, P Yang, Z Yu - IEEE Transactions on Network …, 2023 - ieeexplore.ieee.org
This article is concerned with the issue of improving video subscribers' quality of experience
(QoE) by deploying a multi-unmanned aerial vehicle (UAV) network. Different from existing …

A Lyapunov-Based Approach to Joint Optimization of Resource Allocation and 3D Trajectory for Solar-Powered UAV MEC Systems

XH Lin, S Bi, G Su, YJA Zhang - IEEE Internet of Things Journal, 2024 - ieeexplore.ieee.org
Due to its agility, reusability, and programmability, the unmanned aerial vehicle (UAV) can
be utilized as a flying base station in mobile edge computing (MEC) systems, providing cost …

[PDF][PDF] Prescriptive Maintenance and Operation with Deep Reinforcement Learning

T Yuan - 2023 - research-collection.ethz.ch
Although predictive maintenance has improved the availability of industrial systems by
predicting the remaining useful life and scheduling maintenance actions in a timely manner …

Multi-Access Edge Computing for UAVs Cooperation in Power System

W Wang, H Zhu, D Zhou, L Wei, Y Xu… - 2022 IEEE 6th …, 2022 - ieeexplore.ieee.org
Multi-access edge computing (MEC) uses unmanned aerial vehicles (UAVs) as edge nodes
for dynamic deployment, which can cover complex environments and greatly enhance the …