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 …
sensitive tasks have emerged in large numbers, which impose higher requirements on the …
[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 …
increase in the amount of request computation tasks generated by intelligent wireless …
Joint task offloading and resource allocation for mobile edge computing in ultra-dense network
Mobile edge computing (MEC) enabled user-centric ultra-dense network (UDN) is a
promising solution to the energy constrained mobile users with delay-sensitive and …
promising solution to the energy constrained mobile users with delay-sensitive and …
Federated Deep Reinforcement Learning-based task offloading system in edge computing environment
H Merakchi, M Bagaa, AO Messaoud… - … 2023-2023 IEEE …, 2023 - ieeexplore.ieee.org
Nowadays, Internet of Things (IoT) devices are gaining momentum globally. However, due
to their limited size, these devices have limited battery capacity, computational resources …
to their limited size, these devices have limited battery capacity, computational resources …
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 …
Things (IoT) devices in processing computation-intensive tasks. However, because of the …
Joint wireless source management and task offloading in ultra-dense network
S Pang, S Wang - IEEE Access, 2020 - ieeexplore.ieee.org
The ultra-dense network (UDN) based on mobile edge computing (MEC) is an important
technology, which can achieve the low-latency of 5G communications and enhance the …
technology, which can achieve the low-latency of 5G communications and enhance the …
Collaborative task offloading and resource scheduling framework for heterogeneous edge computing
J Ren, T Hou, H Wang, H Tian, H Wei, H Zheng… - Wireless …, 2021 - Springer
With the continuous development and maturity of the fifth-generation mobile network (5G)
technology, the demand for multimedia service access is increasing, which poses huge …
technology, the demand for multimedia service access is increasing, which poses huge …
Energy-efficient task offloading for semantic-aware networks
The limited computation capacity of user equipments restricts the local implementation of
computation-intense applications. Edge computing, especially the edge intelligence system …
computation-intense applications. Edge computing, especially the edge intelligence system …
Deep reinforcement learning aided task partitioning and computation offloading in mobile edge computing
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 …
wireless networks. To better support the Quality of Service of IoT devices with constrained …
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 …
the edge server (s) to save time and energy. However, we should consider many dynamic …