分层图注意力网络实现大规模无人机防撞，兼顾实时性与抗攻击能力。
Hierarchical Federated Graph Attention Networks for Scalable and Resilient UAV Collision Avoidance
- 三层架构：本地低延迟、区域联邦学习、全局轻量共识，计算复杂度降为O(nk)
- 500架无人机时碰撞率低于2%，支持超过n/3的拜占庭故障容错
- 动态差分隐私调节噪声，实测95%决策响应在50ms内完成
实时性能、抗干扰能力和隐私保护是大规模多无人机系统中实现防撞的核心指标。现有框架常采用单体式设计，不仅计算开销巨大（复杂度O(n²)），且缺乏拜占庭容错能力。本文提出一种分层架构，将智能分为三层：本地层采用密集图注意力机制，延迟低于10ms；区域层使用稀疏注意力和坐标修剪平均聚合的异步联邦学习，复杂度为O(nk)；全局层则基于轻量级哈希图协议。提出自适应差分隐私机制，噪声水平ε∈[0.1,1.0]随实时威胁评估动态下调，以最大化隐私-效用权衡。采用基于分布式哈希表的轻量审计日志替代重区块链共识，所有测试蜂群规模下，95百分位决策延迟均控制在50ms以内。该架构可支持500架无人机场景，碰撞率低于2.0%，具备f < n/3的拜占庭容错能力。
原文摘要 · Abstract (English)
The real-time performance, adversarial resiliency, and privacy preservation are the most important metrics that need to be balanced to practice collision avoidance in large-scale multi-UAV (Unmanned Aerial Vehicle) systems. Current frameworks tend to prescribe monolithic solutions that are not only prohibitively computationally complex with a scaling cost of $O(n^2)$ but simply do not offer Byzantine fault tolerance. The proposed hierarchical framework presented in this paper tries to eliminate such trade-offs by stratifying a three-layered architecture. We spread the intelligence into three layers: an immediate collision avoiding local layer running on dense graph attention with latency of $<10 ms$, a regional layer using sparse attention with $O(nk)$ computational complexity and asynchronous federated learning with coordinate-wise trimmed mean aggregation, and lastly, a global layer using a lightweight Hashgraph-inspired protocol. We have proposed an adaptive differential privacy mechanism, wherein the noise level $(ε\in [0.1, 1.0])$ is dynamically reduced based on an evaluation of the measured real-time threat that in turn maximized the privacy-utility tradeoff. Through the use of Distributed Hash Table (DHT)-based lightweight audit logging instead of heavyweight blockchain consensus, the median cost of getting a $95^{th}$ percentile decision within 50ms is observed across all tested swarm sizes. This architecture provides a scalable scenario of 500 UAVs with a collision rate of $< 2.0\%$ and the Byzantine fault tolerance of $f < n/3$.
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