Advanced meta-heuristic technique for optimizing communication performance in UAV networks

The development of Unmanned Aerial Vehicle (UAV) networks has revolutionized several sectors, such as emergencies, environmental monitoring, and intelligent agriculture. UAV networks suggest significant benefits in real-time information gathering, remote surveillance, and automation. Yet, achieving optimal communication efficiency in UAV networks is still a major challenge with dynamic network topology, energy constraints, and interference from environmental variables like weather conditions and signal obstructions. Preserving untainted and reliable connectivity for UAV networks is essential for their effective deployment in mission-critical scenarios. The study provides a Hybrid Snow Ablation Shark Nose Optimizer (HSASNO) method to enhance communication performance in UAV networks with focus on performance parameters including latency, energy efficiency, and throughput.The suggested method makes use of nature-based and bio-based optimization methods to adaptively modify the network parameters so as to guarantee adaptive and auto-optimizing communication by UAVs. HSASNO aims to optimize UAV path planning, power transmission management, and resource planning, which will result in a remarkable network performance and stability improvement.Simulations were conducted in diverse scenarios, such as different densities of UAVs, movement styles, and weather conditions, to estimate the robustness of the suggested method. Results show that there is considerable enhancement in network performance with reduced latency, better energy efficiency, and increased data throughput in comparison to conventional schemes. In particular, the HSASNO scheme recorded less energy consumption (24.40), less end-to-end delay (0.98), and increased throughput (0.992), which shows its superiority. The outcomes reflect the effectiveness of meta-heuristic methods in overcoming the inherent complexity of UAV communication in networks. The system as proposed guarantees efficient and reliable communication and flexibility with respect to changes in climatic and operational environments, hence highly suitable for real-world applications, including disaster response, environmental surveillance, and smart transportation systems.