[HTML][HTML] Optimizing task offloading and resource allocation in edge-cloud networks: a DRL approach

I Ullah, HK Lim, YJ Seok, YH Han - Journal of Cloud Computing, 2023 - Springer
Edge-cloud computing is an emerging approach in which tasks are offloaded from mobile
devices to edge or cloud servers. However, Task offloading may result in increased energy …

DMRO: A deep meta reinforcement learning-based task offloading framework for edge-cloud computing

G Qu, H Wu, R Li, P Jiao - IEEE Transactions on Network and …, 2021 - ieeexplore.ieee.org
With the explosive growth of mobile data and the unprecedented demand for computing
power, resource-constrained edge devices cannot effectively meet the requirements of …

Dependency-aware task offloading based on deep reinforcement learning in mobile edge computing networks

J Li, Z Yang, K Chen, Z Ming, X Li, Q Fan, J Hao… - Wireless …, 2023 - Springer
With the rapid development of innovative applications, lots of computation-intensive and
delay-sensitive tasks are emerging. Task offloading, which is regarded as a key technology …

Deep reinforcement learning-based task offloading and resource allocation for mobile edge computing

L Huang, X Feng, L Qian, Y Wu - … , MLICOM 2018, Hangzhou, China, July 6 …, 2018 - Springer
We consider a mobile edge computing system that every user has multiple tasks being
offloaded to edge server via wireless networks. Our goal is to acquire a satisfactory task …

Real-Time Offloading for Dependent and Parallel Tasks in Cloud-Edge Environments Using Deep Reinforcement Learning

X Chen, S Hu, C Yu, Z Chen… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
As an effective technique to relieve the problem of resource constraints on mobile devices
(MDs), the computation offloading utilizes powerful cloud and edge resources to process the …

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 …

Learning for smart edge: Cognitive learning-based computation offloading

Y Hao, Y Jiang, MS Hossain, MF Alhamid… - Mobile Networks and …, 2020 - Springer
With the development of intelligent applications, more and more intelligent applications are
computation intensive, data intensive and delay sensitive. Compared with traditional cloud …

Dynamic task offloading for internet of things in mobile edge computing via deep reinforcement learning

Y Chen, W Gu, K Li - International Journal of Communication …, 2022 - Wiley Online Library
With the development of Internet of Things (IoT), more and more computation‐intensive
tasks are generated by IoT devices. Due to the limitation of battery and computing capacity …

Deep Q-learning enabled joint optimization of mobile edge computing multi-level task offloading

P Yan, S Choudhury - Computer Communications, 2021 - Elsevier
In a mobile edge computing (MEC) network, mobile devices could selectively offload tasks to
the edge server (s) to save time and energy. However, we should consider many dynamic …

An advanced deep reinforcement learning algorithm for three-layer D2D-edge-cloud computing architecture for efficient task offloading in the Internet of Things

K Moghaddasi, S Rajabi, FS Gharehchopogh… - … Informatics and Systems, 2024 - Elsevier
Abstract The Internet of Things (IoTs) has transformed the digital landscape by
interconnecting billions of devices worldwide, paving the way for smart cities, homes, and …