## 2 Related Works  
Various studies [12; 13; 14; 15; 16; 17; 18] focused on developing and analyzing the performance of routing protocols for UAV ad hoc networks, or FANETs. In [12], the author analyzed routing protocols such as the Ad hoc On-Demand Distance Vector (AODV), Destination-Sequenced Distance Vector Routing (DSDV), Dynamic Source Routing (DSR), OLSR, the Ad hoc On-Demand Multipath Distance Vector (AOMDV), and the Hybrid Wireless Mesh Protocol (HWMP) to evaluate their performance in FANETs during real-time operations. Using NS-2 for simulation-based evaluation, it was determined that HWMP and OLSR have the best behavior outcomes in the dynamic settings of FANETs. OLSR has lower overhead costs than HWMP. Therefore, more work must be conducted to minimize overhead. In [13], the authors examined QoS metrics for AODV, OLSR, and HWMP routing protocols in FANETs using the simulation program NS-3. They evaluated proactive, reactive, and hybrid algorithms based on hop count, PDR, Goodput, and overhead metrics for source-to-destination transmission across a swarm of UAVs. The Gauss-Markov (GM) Mobility Model was utilized to mimic the behavior of UAVs inside a swarm. The simulated  
Figure 1: Workflow of the proposed approach. area ranged between 250 and 750 m, and the size of the UAVs was variable. In every simulation scenario, the average QoS metric was determined. In [14], the authors thoroughly evaluated standard ad hoc routing protocols for FANETs, including OLSR, AODV, DSR, the Temporally Ordered Routing Algorithm (TORA), and Geographic Probabilistic Routing (GRP). Using a network simulator (OPNET 17.5), the performance of these protocols was examined. Further, the performance of protocols was compared based on the ratio of packets, delay, number of hops, and throughput for various movement speeds and mobility models. Across all evaluation scenarios, the simulation results showed that OLSR and GRP perform better on average than AODV, DSR, and TORA. Their study demonstrates that the variation in network structure, resulting from the relative speeds of nodes, is the primary driver of network performance fluctuations. In [15], the authors simulated the performance of UAV communication networks with several routing methods and network environments and assessed the results. Through the simulation of four types of UAV communication network routing protocols (AODV, DSR, OLSR, and GRP), the metrics of latency, traffic received, dropped data, and throughput were compared. The simulation findings indicate that OLSR has reduced network latency and greater throughput, while the routing protocol of DSR has higher traffic received and the routing protocol of AODV has fewer data lost. Diverse routing algorithms have varying performances in UAV ad hoc networks depending on the UAV density and UAV flying speed. In [16], the authors evaluated the effectiveness of four topology-based routing protocols (DSR, AODV, GRP, and OLSR) by using the simulation program OPNET 14.5. Several metrics, including delay, throughput, and data loss rate, were utilized in performance evaluation. The authors also suggested an enhanced version of OLSR (E-OLSR) by adjusting parameters and decreasing holding time. In the simulation, the optimized E-OLSR settings outperformed the standard OLSR, making it acceptable for usage in UAV ad hoc network (UANET) scenarios. Simulation findings showed that E-OLSR outperforms the classical OLSR and trumps the other protocols discussed in their study. In terms of latency, the OLSR protocol outperforms the Ad hoc On-Demand Distance Vector (AODV) protocol. In [17], the authors suggested the Cross-Layer and Energy-Aware AODV (CLEA-AODV) routing algorithm to enhance FANET efficiency. The three primary components of the CLEA-AODV protocol are: (1) cooperative medium access control, (2) glow swarm optimization (GSO), and (3) forwarding with the AODV protocol (MAC).