Deep Reinforcement Learning for QoE-Aware Offloading in Space-Terrestrial Integrated Networks

X Deng, G Lin, L Chang, F Tong - 2023 19th International …, 2023 - ieeexplore.ieee.org
Low Earth Orbit (LEO) satellite-based edge computing offers an innovative paradigm for
offloading the computing tasks of resource-limited User Equipments (UEs) in the …

Task Offloading With Service Migration for Satellite Edge Computing: A Deep Reinforcement Learning Approach

H Wu, X Yang, Z Bu - IEEE Access, 2024 - ieeexplore.ieee.org
Satellite networks with edge computing servers promise to provide ubiquitous and low-
latency computing services for the Internet of Things (IoT) applications in the future satellite …

Deep reinforcement learning-based task offloading in satellite-terrestrial edge computing networks

D Zhu, H Liu, T Li, J Sun, J Liang… - 2021 IEEE Wireless …, 2021 - ieeexplore.ieee.org
In remote regions (eg, mountain and desert), cellular networks are usually sparsely
deployed or unavailable. With the appearance of new applications (eg, industrial automation …

A Policy based Deep Reinforcement Learning for Task Offloading and Resource Allocation in Satellite Terrestrial Integrated Internet of Things

H Wang, Z Yan, Q Tan, K Li, K Zhao… - 2023 6th World …, 2023 - ieeexplore.ieee.org
Onboard computational resources can be deployed on low earth orbit (LEO) satellites to
provide multi-access edge computing (MEC) in a satellite terrestrial integrated Internet of …

Deep Deterministic Policy Gradient Algorithm for Space/Aerial-Assisted Computation Offloading

J Fu, L Liang, Y Li, J Wang - … on Communications and Networking in China, 2021 - Springer
Abstract Space-air-ground integrated network (SAGIN) has been envisioned as a promising
architecture and computation offloading is a challenging issue, with the growing demand for …

Satellite-assisted edge computing management based on deep reinforcement learning in industrial internet of things

Y Zhu, D Lu - Computer Networks, 2023 - Elsevier
The insufficient edge computing equipment in remote areas cannot meet explosively
growing computing needs of industrial Internet of things devices, which undoubtedly leads to …

Dynamic User Association and Computation Offloading in Satellite Edge Computing Networks via Deep Reinforcement Learning

H Zhang, H Zhao, R Liu, X Gao… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Satellite mobile edge computing (SMEC) deployed on ultra-dense low Earth orbit (LEO)
satellites with high throughput and low latency can provide ubiquitous computing services …

Multi-agent reinforcement learning aided computation offloading in aerial computing for the internet-of-things

Z Qin, H Yao, T Mai, D Wu, N Zhang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
LEO satellite networks have become a necessary supplement to terrestrial networks aiming
to provide worldwide, ubiquitous connectivity, especially in complicated areas (eg …

Collaborative Task Offloading Optimization for Satellite Mobile Edge Computing Using Multi-Agent Deep Reinforcement Learning

H Zhang, H Zhao, R Liu, A Kaushik… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Satellite mobile edge computing (SMEC) achieves efficient processing for space missions
by deploying computing servers on low Earth orbit (LEO) satellites, which supplements a …

Adaptive Task Offloading with Spatiotemporal Load Awareness in Satellite Edge Computing

J Zhou, Y Zhao, L Zhao, H Cai… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Satellite edge computing, as an extension of ground edge computing, is a key technology for
providing computing services by deploying resources on low earth orbit (LEO) satellites …