A deep learning approach for task offloading in multi-UAV aided mobile edge computing

MA Ebrahim, GA Ebrahim, HK Mohamed… - IEEE …, 2022 - ieeexplore.ieee.org
Computation offloading has proven to be an effective method for facilitating resource-
intensive tasks on IoT mobile edge nodes with limited processing capabilities. Additionally …

Energy-efficient UAV-enabled computation offloading for industrial internet of things: a deep reinforcement learning approach

S Shi, M Wang, S Gu, Z Zheng - Wireless Networks, 2021 - Springer
Abstract Industrial Internet of Things (IIoT) has been envisioned as a killer application of 5G
and beyond. However, due to the shortness of computation ablility and batery capacity, it is …

Digital twin assisted task offloading for aerial edge computing and networks

B Li, Y Liu, L Tan, H Pan… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Considering the user mobility and unpredictable mobile edge computing (MEC)
environments, this paper studies the intelligent task offloading problem in unmanned aerial …

Deep reinforcement learning for computation offloading and resource allocation in unmanned-aerial-vehicle assisted edge computing

S Li, X Hu, Y Du - Sensors, 2021 - mdpi.com
Computation offloading technology extends cloud computing to the edge of the access
network close to users, bringing many benefits to terminal devices with limited battery and …

Deep reinforcement learning-based computation offloading in uav swarm-enabled edge computing for surveillance applications

SMA Huda, S Moh - IEEE Access, 2023 - ieeexplore.ieee.org
The rapid development of the Internet of Things and wireless communication has resulted in
the emergence of many latency-constrained and computation-intensive applications such as …

Task offloading and trajectory control for UAV-assisted mobile edge computing using deep reinforcement learning

L Zhang, ZY Zhang, L Min, C Tang, HY Zhang… - IEEE …, 2021 - ieeexplore.ieee.org
Mobile Edge Computing (MEC) has been widely employed to support various Internet of
Things (IoT) and mobile applications. By leveraging the advantages of easily deployed and …

Multi-agent deep reinforcement learning for task offloading in UAV-assisted mobile edge computing

N Zhao, Z Ye, Y Pei, YC Liang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Mobile edge computing can effectively reduce service latency and improve service quality
by offloading computation-intensive tasks to the edges of wireless networks. Due to the …

Joint task offloading, resource allocation, and trajectory design for multi-uav cooperative edge computing with task priority

H Hao, C Xu, W Zhang, S Yang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Mobile edge computing (MEC) has emerged as a solution to address the demands of
computation-intensive network services by providing computational capabilities at the …

Deep Reinforcement Learning Based Computation Offloading in UAV-Assisted Edge Computing

P Zhang, Y Su, B Li, L Liu, C Wang, W Zhang, L Tan - Drones, 2023 - mdpi.com
Traditional multi-access edge computing (MEC) often has difficulty processing large
amounts of data in the face of high computationally intensive tasks, so it needs to offload …

DeepMECagent: multi-agent computing resource allocation for UAV-assisted mobile edge computing in distributed IoT system

X Zhang, Y Wang - Applied Intelligence, 2023 - Springer
The proliferation of Internet-of-Things (IoTs) devices provides a promising platform for
various intelligent applications such as virtual reality. However, because of the limited …