Multi-agent reinforcement learning based resource management in MEC-and UAV-assisted vehicular networks
In this paper, we investigate multi-dimensional resource management for unmanned aerial
vehicles (UAVs) assisted vehicular networks. To efficiently provide on-demand resource …
vehicles (UAVs) assisted vehicular networks. To efficiently provide on-demand resource …
DDPG-based resource management for MEC/UAV-assisted vehicular networks
In this paper, we investigate joint vehicle association and multi-dimensional resource
management in a vehicular network assisted by multi-access edge computing (MEC) and …
management in a vehicular network assisted by multi-access edge computing (MEC) and …
Multi-agent deep reinforcement learning based UAV trajectory optimization for differentiated services
Driven by the increasing computational demand of real-time mobile applications, Unmanned
Aerial Vehicle (UAV) assisted Multi-access Edge Computing (MEC) has been envisioned as …
Aerial Vehicle (UAV) assisted Multi-access Edge Computing (MEC) has been envisioned as …
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 …
Learning-based computation offloading approaches in UAVs-assisted edge computing
Technological evolutions in unmanned aerial vehicle (UAV) industry have granted UAVs
more computing and storage resources, leading to the vision of UAVs-assisted edge …
more computing and storage resources, leading to the vision of UAVs-assisted edge …
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 …
A multi-agent collaborative environment learning method for UAV deployment and resource allocation
Z Dai, Y Zhang, W Zhang, X Luo… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The dynamic position deployment and resource allocation of the unmanned aerial vehicle
(UAV) communication networks has great significance in terms of interference management …
(UAV) communication networks has great significance in terms of interference management …
Deep reinforcement learning based resource management for multi-access edge computing in vehicular networks
In this paper, we study joint allocation of the spectrum, computing, and storing resources in a
multi-access edge computing (MEC)-based vehicular network. To support different vehicular …
multi-access edge computing (MEC)-based vehicular network. To support different vehicular …
Collaborative computation offloading and resource allocation in multi-UAV-assisted IoT networks: A deep reinforcement learning approach
AM Seid, GO Boateng, S Anokye… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
In the fifth-generation (5G) wireless networks, Edge-Internet-of-Things (EIoT) devices are
envisioned to generate huge amounts of data. Due to the limitation of computation capacity …
envisioned to generate huge amounts of data. Due to the limitation of computation capacity …
Semi-distributed resource management in UAV-aided MEC systems: A multi-agent federated reinforcement learning approach
Recently, unmanned aerial vehicle (UAV)-enabled multi-access edge computing (MEC) has
been introduced as a promising edge paradigm for the future space-aerial-terrestrial …
been introduced as a promising edge paradigm for the future space-aerial-terrestrial …