Arama ve kurtarma görevlerinde çoklu İHA kullanarak ağ sağlama

Teams of UAVs are widely considered for civil applications, where UAVs collaborate as data collection or delivery nodes. For this reason, recent research has proposed UAV path planning algorithms that integrate connectivity as a constraint or optimization objective. However, most studies primarily focus on topological connectivity or average network performance, often using network simulators with randomized or sweeping mobility models to analyze higher-layer protocols. In this thesis, we first analyze the performance of multi-UAV path planners optimized for connectivity, investigating both collaboratively optimized networks and relay-assisted networks. Taking network-optimized multi-UAV paths as input, we show that topologically connected UAV paths do not inherently guarantee acceptable network performance in terms of PDR and throughput. In addition, we develop a trajectory-based scheduling approach that exploits the future movements of UAVs to improve data delivery. By predicting imminent link availability, each node can forward its packets to neighbors that are expected to connect to the BS soon, thereby reducing overall transmission delays. Our results demonstrate that this scheduling and forwarding mechanism can outperform classical hop-based routing (e.g., AODV)——thereby underscoring the importance of incorporating trajectory information into both UAV path planning and data routing for mission-critical applications.