Toward Intelligent Distributed Segment-Based Routing in 6G-Era Ultra-Large-Scale UAV Swarm Networks
In recent years, unmanned aerial vehicle (UAV) swarm networks have been widely utilized across various fields. Moreover, the advent of 6G technologies has rapidly expanded the size of UAV swarm networks, making efficient routing a critical challenge. Nevertheless, most routing methods in UAV swarm networks are IP-based. As the network scales, the methods suffer from significant routing table update overhead, degrading routing performance. To address this issue, we integrate the segment-based routing scheme into ultra-large-scale 6G-enhanced UAV swarm networks, using its adaptive segment ability to reduce routing overhead and improve flexibility and scalability. However, UAV swarm networks are flat and self-organizing, making current centralized segment-based routing methods impractical. To solve that, we propose a distributed segment-based routing framework that divides the UAV swarm network into segments and activates a segment routing over the IPv6 (SRv6) node at each segment boundary for segment-based routing. Based on this, given the high dynamics of UAV swarm networks, we propose a dynamic distributed segment and SRv6 activation mechanism and a distributed intelligent routing method for adaptive segment adjustments and efficient routing. Lastly, we discuss promising future research directions.
Authors
- Zehui Xiong (ORCID: https://orcid.org/0000-0002-4440-941X)
- Tianle Mai (ORCID: https://orcid.org/0000-0002-8500-1461)
- Zunliang Wang (ORCID: https://orcid.org/0000-0002-2147-8850)
- Runlong Zhang
- Dusit Niyato (ORCID: https://orcid.org/0000-0002-7442-7416)
- Haipeng Yao
Institutions
- Beijing University of Posts and Telecommunications (CN)
- Singapore University of Technology and Design (SG)
- Nanyang Technological University (SG)
Publication Details
- Journal
- IEEE Communications Magazine
- Published
- 2025-05-29
- DOI
- https://doi.org/10.1109/mcom.001.2400583
- Citations
- 3
- Primary Topic
- UAV Applications and Optimization
- Type
- article
- Field-Weighted Citation Impact
- 14.98
Funders
- National Natural Science Foundation of China
- National Key Research and Development Program of China