Rozario Anatte, Ahmed Ehasan, Mansoor Nafees
Department of Computer Science and Engineering, University of Liberal Arts Bangladesh (ULAB), Dhaka 1207, Bangladesh.
Sensors (Basel). 2024 Sep 30;24(19):6334. doi: 10.3390/s24196334.
The adoption of UAVs in defence and civilian sectors necessitates robust communication networks. This paper presents a routing protocol for Cognitive Radio Unmanned Aerial Vehicles (CR-UAVs) in Flying Ad-hoc Networks (FANETs). The protocol is engineered to optimize route selection by considering crucial parameters such as distance, speed, link quality, and energy consumption. A standout feature is the introduction of the Central Node Resolution Factor (CNRF), which enhances routing decisions. Leveraging the Received Signal Strength Indicator (RSSI) enables accurate distance estimation, crucial for effective routing. Moreover, predictive algorithms are integrated to tackle the challenges posed by high mobility scenarios. Security measures include the identification of malicious nodes, while the protocol ensures resilience by managing multiple routes. Furthermore, it addresses route maintenance and handles link failures efficiently, cluster formation, and re-clustering with joining and leaving new nodes along with the predictive algorithm. Simulation results showcase the protocol's self-comparison under different packet sizes, particularly in terms of end-to-end delay, throughput, packet delivery ratio, and normalized routing load. However, superior performance compared to existing methods, particularly in terms of throughput and packet transmission delay, underscoring its potential for widespread adoption in both defence and civilian UAV applications.
在国防和民用领域采用无人机需要强大的通信网络。本文提出了一种适用于飞行自组织网络（FANET）中认知无线电无人机（CR-UAV）的路由协议。该协议通过考虑距离、速度、链路质量和能耗等关键参数来优化路由选择。一个突出的特点是引入了中央节点分辨率因子（CNRF），它增强了路由决策。利用接收信号强度指示（RSSI）能够进行精确的距离估计，这对有效路由至关重要。此外，集成了预测算法以应对高移动性场景带来的挑战。安全措施包括识别恶意节点，同时该协议通过管理多条路由确保弹性。此外，它解决了路由维护问题，并有效地处理链路故障、集群形成以及随着新节点加入和离开的重新集群以及预测算法。仿真结果展示了该协议在不同数据包大小下的自我比较，特别是在端到端延迟、吞吐量、数据包交付率和归一化路由负载方面。然而，与现有方法相比具有卓越性能，特别是在吞吐量和数据包传输延迟方面，凸显了其在国防和民用无人机应用中广泛采用的潜力。
