Development of Adaptive Drone Swarm Networks

Drone swarms demonstrate significant advantages in executing complex missions. However, existing systems are constrained by preprogrammed algorithms and rigid communication frameworks, making them less adaptable to dynamic environments. To address this issue, this study proposes “AeroSyn”, a drone swarm network architecture designed to operate efficiently across various communication conditions, ensuring stable and effective communication under different infrastructure constraints. The AeroSyn integrates MQLink and UAVConnector to accommodate different network requirements. MQLink utilizes an event-driven publish-subscribe mechanism, making it suitable for cellular networks by enabling dynamic data exchange and decentralized role adaptation, which is particularly beneficial for high-mobility drone formations. UAVConnector is designed for infrastructure-less environments, ensuring minimal data transmission while allowing UAV swarms to maintain autonomous coordination through a Leader-Follower approach, even when disconnected from ground control stations. By incorporating a dual-mode communication strategy, AeroSyn seamlessly adapts to high-mobility cellular networks and mission-oriented operations in infrastructure-free environments, providing a robust and scalable communication solution. Systematic testing has validated AeroSyn’s adaptability and feasibility, positioning it as a flexible and globally applicable framework for future drone swarm deployments.

Authors

Institutions

Publication Details

Journal
IEEE Access
Published
2025-01-01
DOI
https://doi.org/10.1109/access.2025.3591763
Citations
1
Primary Topic
UAV Applications and Optimization
Type
article
Field-Weighted Citation Impact
4.99
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Development of Adaptive Drone Swarm Networks

Chian-Yu Lu, Shih-Hao Chen, Chun‐Liang Lin, Yangyi Chen et al.
1 citations
IEEE Access
UAV Applications and Optimization
4.99
article

Development of Adaptive Drone Swarm Networks

Chian-Yu Lu, Shih-Hao Chen, Chun‐Liang Lin, Yangyi Chen, Wen-Chun Huang
article en
1 citations

Abstract

Drone swarms demonstrate significant advantages in executing complex missions. However, existing systems are constrained by preprogrammed algorithms and rigid communication frameworks, making them less adaptable to dynamic environments. To address this issue, this study proposes “AeroSyn”, a drone swarm network architecture designed to operate efficiently across various communication conditions, ensuring stable and effective communication under different infrastructure constraints. The AeroSyn integrates MQLink and UAVConnector to accommodate different network requirements. MQLink utilizes an event-driven publish-subscribe mechanism, making it suitable for cellular networks by enabling dynamic data exchange and decentralized role adaptation, which is particularly beneficial for high-mobility drone formations. UAVConnector is designed for infrastructure-less environments, ensuring minimal data transmission while allowing UAV swarms to maintain autonomous coordination through a Leader-Follower approach, even when disconnected from ground control stations. By incorporating a dual-mode communication strategy, AeroSyn seamlessly adapts to high-mobility cellular networks and mission-oriented operations in infrastructure-free environments, providing a robust and scalable communication solution. Systematic testing has validated AeroSyn’s adaptability and feasibility, positioning it as a flexible and globally applicable framework for future drone swarm deployments.

IEEE AccessVol. 13
National Chung Hsing University (TW)
Openalex Percentile: Top 5%
UAV Applications and Optimization
4.99
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.