UAV ad hoc network routing algorithms in space–air–ground integrated networks: Challenges and directions
Y Lu, W Wen, KK Igorevich, P Ren, H Zhang, Y Duan… - Drones, 2023 - mdpi.com
With the rapid development of 5G and 6G communications in recent years, there has been
significant interest in space–air–ground integrated networks (SAGINs), which aim to achieve …
significant interest in space–air–ground integrated networks (SAGINs), which aim to achieve …
Minimum Latency‐Secure Key Transmission for Cloud‐Based Internet of Vehicles Using Reinforcement Learning
V Akilandeswari, A Kumar… - Computational …, 2022 - Wiley Online Library
The Internet of Vehicles (IoV) communication key management level controls the
confidentiality and security of its data, which may withstand user identity‐based attacks such …
confidentiality and security of its data, which may withstand user identity‐based attacks such …
An intelligent cluster-based routing scheme in 5G flying ad hoc networks
Flying ad hoc network (FANET) is an application of 5G access network, which consists of
unmanned aerial vehicles or flying nodes with scarce resources and high mobility rates. This …
unmanned aerial vehicles or flying nodes with scarce resources and high mobility rates. This …
[HTML][HTML] An improved method of AODV routing protocol using reinforcement learning for ensuring QoS in 5G-based mobile ad-hoc networks
TVT Duong - ICT Express, 2024 - Elsevier
Abstract 5G-based MANET has received a lot of attention recently. Its fundamental feature is
that nodes are constantly subjected to high traffic loads, while QoS requirements are …
that nodes are constantly subjected to high traffic loads, while QoS requirements are …
XiA: Send-it-anyway Q-routing for 6G-enabled UAV-LEO communications
In this paper, we propose a delay-aware Q-learning-based routing algorithm-XiA-for sending
data from users to nearest Access Points (APs) through Unmanned Aerial Vehicle (UAV) …
data from users to nearest Access Points (APs) through Unmanned Aerial Vehicle (UAV) …
An Optimization model for service requests management in a 5G network architecture
G Colajanni, D Sciacca - Optimization and Data Science: Trends and …, 2021 - Springer
In this paper, we present a three-tier supply chain network model consisting of a fleet of
UAVs organized as a FANET (Fly ad hoc network) connected one to each other with direct …
UAVs organized as a FANET (Fly ad hoc network) connected one to each other with direct …
Fast and computationally efficient generative adversarial network algorithm for unmanned aerial vehicle–based network coverage optimization
The challenge of dynamic traffic demand in mobile networks is tackled by moving cells
based on unmanned aerial vehicles. Considering the tremendous potential of unmanned …
based on unmanned aerial vehicles. Considering the tremendous potential of unmanned …
[PDF][PDF] Deep Reinforcement Learning for Addressing Disruptions in Traffic Light Control.
This paper investigates the use of multi-agent deep Q-network (MADQN) to address the
curse of dimensionality issue occurred in the traditional multi-agent reinforcement learning …
curse of dimensionality issue occurred in the traditional multi-agent reinforcement learning …
TFACR: A Novel Topology Control Algorithm for Improving 5G-based MANET Performance by Flexibly Adjusting the Coverage Radius
Topology control in next-generation wireless networks has recently attracted the interest of
several researchers. The network performance is significantly affected by the topology …
several researchers. The network performance is significantly affected by the topology …
A systematic approach of a flying ad-hoc network for smart cities
Recently, a flying ad-hoc network (FANET) has been employed in modern warfare for
monitoring and reconnaissance to produce a healthy living environment in smart cities …
monitoring and reconnaissance to produce a healthy living environment in smart cities …