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Smart city article details
| Title | Performance Analysis Of Hybrid Metaheuristic Cross-Layer Optimization Algorithm (Hmcloa) In Uav -Based Iot Networks |
|---|---|
| ID_Doc | 41658 |
| Authors | Rajashekar A.; Chouhan D. |
| Year | 2025 |
| Published | 4th International Conference on Sentiment Analysis and Deep Learning, ICSADL 2025 - Proceedings |
| DOI | http://dx.doi.org/10.1109/ICSADL65848.2025.10933493 |
| Abstract | Optimization in UAV based IoT networks is the most important task for the improvement of network performance, resource utilization, and overall efficiency. UAV -based IoT networks consist of decentralized architecture and dynamic topology. Due to this nature, the network faces challenges like routing, resource allocation, energy efficiency, and Quality of Service (QoS). Addressing these challenges is essential for real-time communication in smart city infrastructure, where UAVs provide reliable and efficient data transmission through free-space communication. Hence, to overcome this research issues, proposed a scheme called 'Hybrid Metaheuristic Cross-Layer Optimization Algorithm (HMCLOA)' finds an energy efficient routing path for an efficient data transmission. A comparative analysis of different optimization approaches highlights their merits and suitability for various network requirements. The major challenges in UAV based IoT networks such as throughput, delay energy consumption, and QoS constraints are discussed, and compared the performance with the existing optimization techniques such as metaheuristic algorithms, cross-layered approaches, and game-theoretic strategies. Finally, it is concluded that the proposed Hybrid Metaheuristic Cross-Layer Optimization Algorithm (HMCLOA) optimization technique helps to improve routing efficiency, resource management, energy consumption, and QoS, thereby enhancing the overall performance and reliability of UAV-based IoT networks. © 2025 IEEE. |
| Author Keywords | Energy Efficiency; Internet of Things; Optimization Techniques; Quality of Service; Unmanned Aerial Vehicles |
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