An expert system for hybrid edge to cloud computational offloading in heterogeneous MEC–MCC environments
Abstract Mobile Cloud Computing (MCC) integrates cloud computing into the mobile
environment, effectively tackling performance, environmental, and security constraints …
environment, effectively tackling performance, environmental, and security constraints …
Deep reinforcement learning-based partial task offloading in high altitude platform-aided vehicular networks
Compared with traditional terrestrial access networks, a mobile edge computing-enabled
aerial access network is a potential paradigm for performing complicated computations by …
aerial access network is a potential paradigm for performing complicated computations by …
Multi-UAV-assisted computation offloading in DT-based networks: A distributed deep reinforcement learning approach
J Shi, C Li, Y Guan, P Cong, J Li - Computer Communications, 2023 - Elsevier
Abstract In the industrial Internet, Mobile Edge Computing (MEC) can provide the ability to
transfer a large number of delay-sensitive and compute-intensive tasks to MEC servers, thus …
transfer a large number of delay-sensitive and compute-intensive tasks to MEC servers, thus …
[HTML][HTML] Survey on computation offloading in UAV-Enabled mobile edge computing
With the increasing growth of internet-of-things (IoT) devices, effective computation
performance has become a critical issue. Many services provided by IoT devices (eg …
performance has become a critical issue. Many services provided by IoT devices (eg …
Cost optimization of UAV-MEC network calculation offloading: A multi-agent reinforcement learning method
J Xue, Q Wu, H Zhang - Ad Hoc Networks, 2022 - Elsevier
Abstract In the Unmanned Aerial Vehicle (UAV)-assisted mobile edge computing (MEC)
system, most existing studies do not effectively consider the task offloading of user …
system, most existing studies do not effectively consider the task offloading of user …
Delay-aware and energy-efficient computation offloading in mobile-edge computing using deep reinforcement learning
Internet of Things (IoT) is considered as the enabling platform for a variety of promising
applications, such as smart transportation and smart city, where massive devices are …
applications, such as smart transportation and smart city, where massive devices are …
Deep reinforcement learning-based computation offloading for servicing dynamic demand in multi-UAV-assisted IoT network
N Lin, L Bai, A Hawbani, Y Guan, C Mao… - IEEE Internet of …, 2024 - ieeexplore.ieee.org
In wireless networks, meeting the performance requirements of all tasks solely with Internet
of Things (IoT) devices is challenging due to their limited computational power and battery …
of Things (IoT) devices is challenging due to their limited computational power and battery …
A cooperative computation offloading strategy with on-demand deployment of multi-UAVs in UAV-aided mobile edge computing
C Li, Y Gan, Y Zhang, Y Luo - IEEE Transactions on Network …, 2023 - ieeexplore.ieee.org
In this paper, we plan to use ground-based stations in mobile edge computing (MEC) and
unmanned aerial vehicles (UAVs) to provide communication and computation offloading …
unmanned aerial vehicles (UAVs) to provide communication and computation offloading …
An efficient online computation offloading approach for large-scale mobile edge computing via deep reinforcement learning
Mobile edge computing (MEC) has been envisioned as a promising paradigm that could
effectively enhance the computational capacity of wireless user devices (WUDs) and quality …
effectively enhance the computational capacity of wireless user devices (WUDs) and quality …
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 …
number of computation tasks (payloads). How to better manage these mobile terminals …