基于预测的自适应扩展卡尔曼SDN-FANET分段混合路由方案
Ke Sun1,2, Mingyong Liu1, Chuan Yin2
1School of Marine Science and Technology, Northwestern Polytechnical University, Xi'an 710072, China.
Sensors (Basel, Switzerland)
|March 17, 2025
概括
本研究介绍了用于飞行特设网络 (FANET) 的混合软件定义网络 (SDN) 路由方案. 拟议的能量平衡和预测路由可以提高高速无人机网络的性能.
科学领域:
- 计算机科学 计算机科学
- 网络工程 网络工程
- 无线通信无线通信
背景情况:
- 飞行特设网络 (FANET) 提供灵活性和多样化的功能,但面临诸如高拓动态和由于高速无人机 (UAV) 运动而导致的数据包丢失等挑战.
- 无人机中的有限节点能量进一步使网络稳定性和性能复杂化.
研究的目的:
- 为了研究软件定义网络 (SDN) 的路由方案,使得FANET (SDN-FANET) 能够利用集中控制.
- 解决高数据包丢失率的问题,并在动态FANET环境中提高路由效率.
主要方法:
- 一个混合SDN架构,包含FANETs的细分路由方案.
- 分段间路由使用能量平衡策略,而分段内路由使用三维 (3D) 贪的周边无状态路由 (GPSR).
- 开发了一种自适应扩展的卡尔曼过算法,用于跟踪和预测3D无人机运动,以减轻数据包丢失.
主要成果:
- 拟议的路由方案有效地管理SDN-FANET内部的分段间和分段内通信.
- 适应式扩展的卡尔曼预测算法成功跟踪和预测无人机运动,减少高速场景中的数据包损失.
- 模拟显示了端到端延迟和数据包交付比率的显著改善.
结论:
- 混合SDN架构为FANET中的路由提供了有效的解决方案,解决了无人机动态带来的挑战.
- 整合能量平衡路由和预测运动跟踪可以提高FANET通信的可靠性和效率.
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