Author:
Yang Siwei,Wang Shu,Li Tingli,Hu Tao,Xu Ziliang,He Renze,Zhang Bing
Abstract
AbstractThis 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.
Publisher
Springer Science and Business Media LLC
Reference28 articles.
1. Li, K., Voicu, R. C., Kanhere, S. S., Ni, W. & Tovar, E. Energy efficient legitimate wireless surveillance of UAV communications. IEEE Trans. Veh. Technol. 68, 2283–2293. https://doi.org/10.1109/TVT.2019.2890999 (2019).
2. Erdelj, M., Natalizio, E., Chowdhury, K. R. & Akyildiz, I. F. Help from the sky: Leveraging UAVs for disaster management. IEEE Pervasive Comput. 16, 24–32. https://doi.org/10.1109/MPRV.2017.11 (2017).
3. Otto, A., Agatz, N., Campbell, J., Golden, B. & Pesch, E. Optimization approaches for civil applications of unmanned aerial vehicles (UAVs) or aerial drones: a survey. Networks. 72, 411–458. https://doi.org/10.1002/net.21818 (2018).
4. Chen, J. et al. Interference-aware online distributed channel selection for multicluster FANET: A potential game approach. IEEE Trans. Veh. Technol. 68, 3792–3804. https://doi.org/10.1109/TVT.2019.2902177 (2019).
5. Huang, W., Chen, J. & Li, Y. Technology survey and development forecast on unmanned aerial vehicle ad hoc networks. Telecommun. Eng. 62, 138–146 (2022).