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用于FANET的基于混合蚁群的簇间路由协议

Hybrid ant colony-based inter-cluster routing protocol for FANET.

作者信息

Yang Siwei, Wang Shu, Li Tingli, Hu Tao, Xu Ziliang, He Renze, Zhang Bing

机构信息

School of Data and Target Engineering, PLA Strategic Support Force Information Engineering University, Zhengzhou, 450001, China.

27Th Research Institute of China Electronics Technology Group Corporation, Zhengzhou, 450001, China.

出版信息

Sci Rep. 2024 Jul 7;14(1):15632. doi: 10.1038/s41598-024-64454-1.

DOI:10.1038/s41598-024-64454-1
PMID:38972887
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11228038/
Abstract

This study addresses the challenges in large-scale unmanned aerial vehicle (UAV) clusters, specifically the scalability issues and limitations of using reactive routing protocols for inter-cluster routing. These traditional methods place an excessive burden on cluster heads and struggle to adapt to frequently changing topologies, leading to decreased network performance. To solve these problems, we propose an innovative inter-cluster routing protocol (ICRP), which is based on a hybrid ant colony algorithm. During the route establishment phase, ICRP uses this algorithm to identify the optimal relay node. This approach is inspired by the foraging behavior of Physarum polycephalum, combining factors such as the number of hops from the source node, the load condition of the node, and its weight in the pheromone calculation. In the route maintenance phase, ICRP uses a predictive repair and contraction mechanism to dynamically maintain routes, accommodating the high mobility of UAVs. Comparative simulations in OMNeT +  + showed that this protocol surpasses ad-hoc on-demand distance vector (AODV), fuzzy-logic-assisted-AODV, and Enhanced-Ant-AODV routing protocols in packet delivery rate and end-to-end transmission delay. Furthermore, it showed superior adaptation to network environments with high-speed node mobility.

摘要

本研究探讨了大规模无人机（UAV）集群中的挑战，特别是可扩展性问题以及在集群间路由中使用反应式路由协议的局限性。这些传统方法给簇头发放了过重负担，并且难以适应频繁变化的拓扑结构，从而导致网络性能下降。为了解决这些问题，我们提出了一种创新的集群间路由协议（ICRP），该协议基于混合蚁群算法。在路由建立阶段，ICRP使用此算法来确定最优中继节点。这种方法的灵感来自多头绒泡菌的觅食行为，它综合了诸如源节点的跳数、节点的负载状况及其在信息素计算中的权重等因素。在路由维护阶段，ICRP使用预测性修复和收缩机制来动态维护路由，以适应无人机的高移动性。在OMNeT++中进行的对比模拟表明，该协议在分组交付率和端到端传输延迟方面优于按需距离矢量路由协议（AODV）、模糊逻辑辅助AODV以及增强蚁群AODV路由协议。此外，它在适应高速节点移动性的网络环境方面表现出色。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d66/11228038/e926b607569d/41598_2024_64454_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d66/11228038/48aa4433aa1e/41598_2024_64454_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d66/11228038/033666fe407f/41598_2024_64454_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d66/11228038/64d67ac847ce/41598_2024_64454_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d66/11228038/1648b2fe86d7/41598_2024_64454_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d66/11228038/333171c59e07/41598_2024_64454_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d66/11228038/b132e854ada8/41598_2024_64454_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d66/11228038/8272abce83e6/41598_2024_64454_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d66/11228038/7be8b225657f/41598_2024_64454_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d66/11228038/344ccff672c4/41598_2024_64454_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d66/11228038/e926b607569d/41598_2024_64454_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d66/11228038/48aa4433aa1e/41598_2024_64454_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d66/11228038/033666fe407f/41598_2024_64454_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d66/11228038/64d67ac847ce/41598_2024_64454_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d66/11228038/1648b2fe86d7/41598_2024_64454_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d66/11228038/333171c59e07/41598_2024_64454_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d66/11228038/b132e854ada8/41598_2024_64454_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d66/11228038/8272abce83e6/41598_2024_64454_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d66/11228038/7be8b225657f/41598_2024_64454_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d66/11228038/344ccff672c4/41598_2024_64454_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d66/11228038/e926b607569d/41598_2024_64454_Fig10_HTML.jpg

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