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软件定义的无人机集群弹性组网架构

甘良棋 董超 朱小军 王蔚

国防科技大学学报2026,Vol.48Issue(4):89-96,8.
国防科技大学学报2026,Vol.48Issue(4):89-96,8.DOI:10.11887/j.issn.1001-2486.25060024

软件定义的无人机集群弹性组网架构

Software-defined resilient networking architecture for UAV swarms

甘良棋 1董超 1朱小军 2王蔚3

作者信息

  • 1. 南京航空航天大学 电子信息工程学院,江苏南京 211106||南京航空航天大学 电磁频谱空间认知动态系统重点实验室,江苏南京 211106
  • 2. 南京航空航天大学 计算机科学与技术学院,江苏南京 211106
  • 3. 南京航空航天大学 电子信息工程学院,江苏南京 211106
  • 折叠

摘要

Abstract

To enhance the sustained mission capability of large-scale UAV(unmanned aerial vehicle)swarms facing both soft and hard-kill threats,this research focused on swarm topology reconstruction methods.Addressing the issue of node failures,a dynamic control authority migration mechanism under a centralized-distributed hybrid control architecture was proposed to improve reconstruction efficiency;concurrently,an SDN(software-defined network)-based elastic networking architecture was designed,integrating intent-driven principles to enable intelligent and dynamic configuration of network resources.Simulation comparisons were conducted between dual-mode reconstruction strategies:neighbor autonomous compensation and resource-pool dynamic scheduling.When facing small-scale node loss,neighbor compensation leverages its advantage in local decision-making,reducing the average reconstruction latency by 38.5%compared to resource-pool scheduling.However,as the number of failed nodes increases,the combined centralized-distributed controller strategy achieves the shortest reconstruction time;notably,under persistent electromagnetic interference environments,this combined strategy demonstrates significant advantages,reducing latency by 18.3%compared to a purely distributed approach.This research provides theoretical support and practical reference for topology reconstruction in large-scale UAV swarms.

关键词

无人机集群/软硬杀伤/软件定义网络/拓扑重构/意图驱动

Key words

unmanned aerial vehicle swarms/soft and hard kill/software-defined network/topology reconfiguration/intent-driven

分类

信息技术与安全科学

引用本文复制引用

甘良棋,董超,朱小军,王蔚..软件定义的无人机集群弹性组网架构[J].国防科技大学学报,2026,48(4):89-96,8.

基金项目

国家自然科学基金资助项目(61931011) (61931011)

国防科技大学学报

1001-2486

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