Deep reinforcement learning based dynamic trajectory control for UAV-assisted mobile edge computing
In this paper, we consider a platform of flying mobile edge computing (F-MEC), where
unmanned aerial vehicles (UAVs) serve as equipment providing computation resource, and …
unmanned aerial vehicles (UAVs) serve as equipment providing computation resource, and …
Task offloading and trajectory control for UAV-assisted mobile edge computing using deep reinforcement learning
L Zhang, ZY Zhang, L Min, C Tang, HY Zhang… - IEEE …, 2021 - ieeexplore.ieee.org
Mobile Edge Computing (MEC) has been widely employed to support various Internet of
Things (IoT) and mobile applications. By leveraging the advantages of easily deployed and …
Things (IoT) and mobile applications. By leveraging the advantages of easily deployed and …
Multi-agent deep reinforcement learning-based trajectory planning for multi-UAV assisted mobile edge computing
An unmanned aerial vehicle (UAV)-aided mobile edge computing (MEC) framework is
proposed, where several UAVs having different trajectories fly over the target area and …
proposed, where several UAVs having different trajectories fly over the target area and …
Evolutionary multi-objective reinforcement learning based trajectory control and task offloading in UAV-assisted mobile edge computing
This article studies the trajectory control and task offloading (TCTO) problem in an
unmanned aerial vehicle (UAV)-assisted mobile edge computing system, where a UAV flies …
unmanned aerial vehicle (UAV)-assisted mobile edge computing system, where a UAV flies …
Path planning for UAV-mounted mobile edge computing with deep reinforcement learning
In this letter, we study an unmanned aerial vehicle (UAV)-mounted mobile edge computing
network, where the UAV executes computational tasks offloaded from mobile terminal users …
network, where the UAV executes computational tasks offloaded from mobile terminal users …
Multi-agent deep reinforcement learning for task offloading in UAV-assisted mobile edge computing
Mobile edge computing can effectively reduce service latency and improve service quality
by offloading computation-intensive tasks to the edges of wireless networks. Due to the …
by offloading computation-intensive tasks to the edges of wireless networks. Due to the …
Computation offloading optimization for UAV-assisted mobile edge computing: a deep deterministic policy gradient approach
Abstract Unmanned Aerial Vehicle (UAV) can play an important role in wireless systems as it
can be deployed flexibly to help improve coverage and quality of communication. In this …
can be deployed flexibly to help improve coverage and quality of communication. In this …
Multi-UAV mobile edge computing and path planning platform based on reinforcement learning
Unmanned Aerial vehicles (UAVs) are widely used as network processors in mobile
networks, but more recently, UAVs have been used in Mobile Edge Computing as mobile …
networks, but more recently, UAVs have been used in Mobile Edge Computing as mobile …
Task offloading for UAV-based mobile edge computing via deep reinforcement learning
With rapid increase of data processing demands from users in mobile edge computing
(MEC), the conventional mobile edge servers (MESs) are no longer capable of providing …
(MEC), the conventional mobile edge servers (MESs) are no longer capable of providing …
A novel Lyapunov based dynamic resource allocation for UAVs-assisted edge computing
Mobile edge computing (MEC), as a key component in the development of IoT and 5G
technologies, can provide extra computation resources in edge servers for mobile devices to …
technologies, can provide extra computation resources in edge servers for mobile devices to …