
Research Article
Research on Intelligent Distributed and Self-adaptive Networking Technology for Manned/Unmanned Collaboration
@INPROCEEDINGS{10.1007/978-3-032-33662-0_22, author={Mengfan Wang and Tengfei Li and Jufeng Fei and Mingqi Li and Jiajian Pan}, title={Research on Intelligent Distributed and Self-adaptive Networking Technology for Manned/Unmanned Collaboration}, proceedings={Communications and Networking. 20th EAI International Conference, ChinaCom 2025, Xi’an, China, November 8--9, 2025, Proceedings}, proceedings_a={CHINACOM}, year={2026}, month={10}, keywords={Unmanned Aerial Vehicle (UAV) Adaptive Networking Collaboration Resource Allocation}, doi={10.1007/978-3-032-33662-0_22} }- Mengfan Wang
Tengfei Li
Jufeng Fei
Mingqi Li
Jiajian Pan
Year: 2026
Research on Intelligent Distributed and Self-adaptive Networking Technology for Manned/Unmanned Collaboration
CHINACOM
Springer
DOI: 10.1007/978-3-032-33662-0_22
Abstract
With the rapid advancement of unmanned aerial vehicle (UAV) technology, UAVs are widely used in surveying and mapping, geographic information systems, agricultural protection, security, emergency response, logistics, and transportation. They play an increasingly significant role, particularly in unmanned combat operations. The increasing technical requirements for autonomy, intelligence, efficiency, and collaboration in UAV missions have accelerated the shift toward multi-UAV operations. As one of the key technologies enabling collaborative missions, distributed data link adaptive networking technology must be enhanced to improve the capability of intelligent collaborative operations in manned/unmanned systems. Therefore, to address the sudden changes in information volume during multi-UAV missions and meet the demands of dynamically varying service data during transmission and relay among nodes in a collaborative network data link, this paper proposes a resource allocation method based on service requirements. This approach ensures quality of service (QoS) for multi-node and multi-service concurrency under limited bandwidth resources. The proposed method significantly improves bandwidth utilization while maintaining low algorithmic complexity, making it suitable for practical engineering applications.

