基于改进泛洪路由协议的蜂群无人机网络:随机网络编码与聚类

Hao Song, Lingjia Liu, Bodong Shang, Scott M. Pudlewski, E. Bentley
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引用次数: 6

摘要

现有的路由协议由于其网络拓扑结构是动态的,且缺乏准确的位置信息,可能无法适用于无人机网络。针对蜂群无人机网络,设计了一种基于随机网络编码(RNC)和聚类的增强型泛洪路由协议,使其在不需要发现路由路径和网络拓扑信息的情况下实现高效路由。RNC可以自然地加速路由过程,在一些跳数中需要传输的代更少。为了解决跳数多的问题并进一步加快路由过程,利用了一种聚类方法,其中无人机网络被划分为多个集群,并且代仅从每个集群的代表中淹没,而不是从每个无人机中淹没。通过这种方式,啤酒花的数量可以显著减少。对引入的路由协议的技术细节进行了设计。此外,为了捕获动态网络拓扑,采用泊松聚类过程对无人机网络进行建模。然后,利用随机几何工具推导了随机选择的两架无人机之间的距离分布,并对其性能进行了分析评估。大量的仿真研究证明了性能分析的有效性,展示了我们设计的路由协议的有效性,并揭示了其设计见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhanced Flooding-Based Routing Protocol for Swarm UAV Networks: Random Network Coding Meets Clustering
Existing routing protocols may not be applicable in UAV networks because of their dynamic network topology and lack of accurate position information. In this paper, an enhanced flooding-based routing protocol is designed based on random network coding (RNC) and clustering for swarm UAV networks, enabling the efficient routing process without any routing path discovery or network topology information. RNC can naturally accelerate the routing process, with which in some hops fewer generations need to be transmitted. To address the issue of numerous hops and further expedite routing process, a clustering method is leveraged, where UAV networks are partitioned into multiple clusters and generations are only flooded from representatives of each cluster rather than flooded from each UAV. By this way, the amount of hops can be significantly reduced. The technical details of the introduced routing protocol are designed. Moreover, to capture the dynamic network topology, the Poisson cluster process is employed to model UAV networks. Afterwards, stochastic geometry tools are utilized to derive the distance distribution between two random selected UAVs and analytically evaluate performance. Extensive simulation studies are conducted to prove the validation of performance analysis, demonstrate the effectiveness of our designed routing protocol, and reveal its design insight.
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