Path planning for UAV communication networks: Related technologies, solutions, and opportunities

J Luo, Z Wang, M Xia, L Wu, Y Tian, Y Chen - ACM Computing Surveys, 2023 - dl.acm.org
Path planning has been a hot and challenging field in unmanned aerial vehicles (UAV). With
the increasing demand of society and the continuous progress of technologies, UAV …

Application relocation in an edge-enabled 5G system: Use cases, architecture, and challenges

G Panek, I Fajjari, H Tarasiuk… - IEEE …, 2022 - ieeexplore.ieee.org
With the growing development of 5G and its new services, edge computing is becoming the
cornerstone of the ongoing network transformation. Its integration into 5G network …

Supporting UAVs with Edge Computing: A Review of Opportunities and Challenges

M Janßen, T Pfandzelter, M Wang… - arXiv preprint arXiv …, 2023 - arxiv.org
Over the last years, Unmanned Aerial Vehicles (UAVs) have seen significant advancements
in sensor capabilities and computational abilities, allowing for efficient autonomous …

Cloud service selection in IoFT-enabled Multi-access Edge Computing: a Game Theoretic approach

SY Brahimi, F Mouffak, FZ Bousbaa… - Annals of …, 2023 - Springer
Abstract Nowadays, Multi-access Edge Computing (MEC) and Internet of Flying Things
(IoFT) clouds are attracting significant attention from both academic and industrial research …

Task offloading in uav swarm-based edge computing: Grouping and role division

W Huang, H Guo, J Liu - 2021 IEEE Global Communications …, 2021 - ieeexplore.ieee.org
Due to the outstanding characteristics of unmanned aerial vehicles (UAV), ie,
maneuverability and flexibility, UAV enabled mobile edge computing (MEC) has become a …

On using deep reinforcement learning to dynamically derive 5G new radio TDD pattern

M Bagaa, K Boutiba, A Ksentini - 2021 IEEE Global …, 2021 - ieeexplore.ieee.org
The deployment of 5G and 6G is highly motivated by the emerging network services that
demand more band-width and very low latency. Besides, these services are shifting from …

Joint task offloading and resource allocation for MEC networks considering UAV trajectory

X Chen, Y Liao, Q Ai, K Zhang - 2021 17th International …, 2021 - ieeexplore.ieee.org
Owing to the high flexibility and mobility, unmanned aerial vehicles (UAVs) have attracted
significant attention from both academia and industry communities, especially in the …

Multi-Agent Deep Reinforcement Learning to enable dynamic TDD in a multi-cell environment

K Boutiba, M Bagaa, A Ksentini - IEEE Transactions on Mobile …, 2023 - ieeexplore.ieee.org
Dynamic Time Division Duplex (D-TDD) is a promising solution to address newly emerging
5G and 6G services characterized by asymmetric and dynamic uplink (UL) and downlink …

5g-edge relocator: a framework for application relocation in edge-enabled 5g system

G Panek, P Matysiak, NE Nouar… - ICC 2023-IEEE …, 2023 - ieeexplore.ieee.org
The convergence of 5G and Edge computing is fostering the development of innovative use
cases making the dream of a fully connected, intelligent digital world almost true. However …

RL-Edge Relocator: a Reinforcement Learning based approach for Application Relocation in Edge-enabled 5G System

G Panek, NE Nouar, I Fajjari… - … 2023-2023 IEEE …, 2023 - ieeexplore.ieee.org
The convergence of 5G and Edge computing has revolutionized the technology landscape,
ushering in a new era of innovative use cases and accelerating the realization of an …