Joint offloading and resource allocation for hybrid cloud and edge computing in SAGINs: A decision assisted hybrid action space deep reinforcement learning …

C Huang, G Chen, P Xiao, Y Xiao, Z Han… - IEEE Journal on …, 2024 - ieeexplore.ieee.org
In recent years, the amalgamation of satellite communications and aerial platforms into
space-air-ground integrated network (SAGINs) has emerged as an indispensable area of …

Resource offload consolidation based on deep-reinforcement learning approach in cyber-physical systems

MS Mekala, A Jolfaei, G Srivastava… - … on Emerging Topics …, 2020 - ieeexplore.ieee.org
In cyber-physical systems, it is advantageous to leverage cloud with edge resources to
distribute the workload for processing and computing user data at the point of generation …

Multiagent Reinforcement Learning for Task Offloading of Space/Aerial‐Assisted Edge Computing

Y Li, L Liang, J Fu, J Wang - Security and Communication …, 2022 - Wiley Online Library
The task offloading in space‐aerial‐ground integrated network (SAGIN) has been
envisioned as a challenging issue. In this paper, we investigate a space/aerial‐assisted …

Deep-deterministic policy gradient based multi-resource allocation in edge-cloud system: a distributed approach

A Qadeer, MJ Lee - IEEE Access, 2023 - ieeexplore.ieee.org
Edge Cloud (EC) empowers the beyond 5G (B5G) wireless networks to cope with large-
scale and real-time traffics of Internet-of-Things (IoT) by minimizing the latency and providing …

Deep reinforcement learning for computation offloading and resource allocation in satellite-terrestrial integrated networks

H Wu, X Yang, Z Bu - 2022 IEEE 95th Vehicular Technology …, 2022 - ieeexplore.ieee.org
Satellite mobile edge computing (SMEC) enhanced satellite-terrestrial integrated networks
(STIN) have attracted intensive attention to obtain seamless coverage and provide on …

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 …

DDPG-edge-cloud: A deep-deterministic policy gradient based multi-resource allocation in edge-cloud system

A Qadeer, MJ Lee - … on Artificial Intelligence in Information and …, 2022 - ieeexplore.ieee.org
5G and beyond is the key enabler for extreme mobile-broadband (xMBB), Massive and Ultra-
reliable machine-type communication (mMTC, uMTC). To handle such large-scale and real …

Multi-agent deep reinforcement learning for cooperative offloading in cloud-edge computing

A Suzuki, M Kobayashi - ICC 2022-IEEE International …, 2022 - ieeexplore.ieee.org
Edge computing is a new paradigm to provide computing capability at the edges close to
end devices. A significant research challenge in edge computing is finding an efficient task …

Curriculum reinforcement learning-based computation offloading approach in space-air-ground integrated network

Z Wang, H Yu, S Zhu, B Yang - 2021 13th International …, 2021 - ieeexplore.ieee.org
Space-air-ground integrated network (SAGIN) is emerging as a prominent framework
supporting the ever-growing Internet of Things (IoT) applications in the areas without …

Deep reinforcement learning approach for uav-assisted mobile edge computing networks

S Hwang, J Park, H Lee, M Kim… - GLOBECOM 2022-2022 …, 2022 - ieeexplore.ieee.org
This paper studies a deep reinforcement learning (DRL) approach for the unmanned aerial
vehicle (UAV)-assisted mobile edge computing (MEC) networks where a UAV-mounted …