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&...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11091317/ |
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| Summary: | 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. |
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| ISSN: | 2169-3536 |