Optimizing Mobility-Aware Task Offloading in Smart Healthcare for Internet of Medical Things Through Multi-Agent Reinforcement Learning

C Dong, Y Sun, M Shafiq, N Hu, Y Liu… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
In the scenario of smart healthcare applications, the Internet of Medical Things (IoMT)
devices, equipped with limited resources, would offload numerous computation-heavy tasks …

Associative tasks computing offloading scheme in Internet of medical things with deep reinforcement learning

J Fan, Q Junwei, L Lei, T Hui - China Communications, 2024 - ieeexplore.ieee.org
The Internet of Medical Things (IoMT) is regarded as a critical technology for intelligent
healthcare in the foreseeable 6G era. Nevertheless, due to the limited computing power …

[HTML][HTML] Fuzzy-assisted mobile edge orchestrator and sarsa learning for flexible offloading in heterogeneous iot environment

TT Khanh, TH Hai, MD Hossain, EN Huh - Sensors, 2022 - mdpi.com
In the era of heterogeneous 5G networks, Internet of Things (IoT) devices have significantly
altered our daily life by providing innovative applications and services. However, these …

[HTML][HTML] Multi-agent deep reinforcement learning-based partial task offloading and resource allocation in edge computing environment

H Ke, H Wang, H Sun - Electronics, 2022 - mdpi.com
In the dense data communication environment of 5G wireless networks, with the dramatic
increase in the amount of request computation tasks generated by intelligent wireless …

Value-based multi-agent deep reinforcement learning for collaborative computation offloading in internet of things networks

H Li, S Meng, J Shang, A Huang, Z Cai - Wireless Networks, 2023 - Springer
As a promising computing paradigm, mobile edge computing (MEC) can assist Internet of
Things (IoT) devices in processing computation-intensive tasks. However, because of the …

Optimizing mobile edge computing multi-level task offloading via deep reinforcement learning

P Yan, S Choudhury - ICC 2020-2020 IEEE International …, 2020 - ieeexplore.ieee.org
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 intelligent task offloading method based on multi-agent deep reinforcement learning in ultra-dense heterogeneous network with mobile edge computing

S Pang, T Wang, H Gui, X He, L Hou - Computer Networks, 2024 - Elsevier
With the rapid development of IoT technology, various computation-intensive and latency-
sensitive tasks have emerged in large numbers, which impose higher requirements on the …

NOMA-based multi-user mobile edge computation offloading via cooperative multi-agent deep reinforcement learning

Z Chen, L Zhang, Y Pei, C Jiang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Mobile edge computing (MEC) is a promising solution to enable resource-limited mobile
devices to offload computation-intensive tasks to nearby edge servers. In this paper …

Adaptive computation offloading policy for multi-access edge computing in heterogeneous wireless networks

H Ke, H Wang, W Sun, H Sun - IEEE Transactions on Network …, 2021 - ieeexplore.ieee.org
In heterogeneous wireless networks, massive mobile terminals randomly generate a large
number of computation tasks (payloads). How to better manage these mobile terminals …

Deep reinforcement learning aided task partitioning and computation offloading in mobile edge computing

L Ale, SA King, N Zhang… - 2021 IEEE/CIC …, 2021 - ieeexplore.ieee.org
With the wave of the Internet of Things (IoT), a vast number of IoT devices are connected to
wireless networks. To better support the Quality of Service of IoT devices with constrained …