Wadhwa Shivani, Gupta Divya, Rani Shalli, Driss Maha, Boulila Wadii
Institute of Engineering and Technology, Chitkara University, Punjab, India.
Department of Computer Science and Engineering, Chandigarh University, Mohali, India.
PLoS One. 2025 Jan 24;20(1):e0314420. doi: 10.1371/journal.pone.0314420. eCollection 2025.
The performance of drones, especially for time-sensitive tasks, is critical in various applications. Fog nodes strategically placed near IoT devices serve as computational resources for drones, ensuring quick service responses for deadline-driven tasks. However, the limited battery capacity of drones poses a challenge, necessitating energy-efficient Internet of Drones (IoD) systems. Despite the increasing demand for drone flying automation, there is a significant absence of a comprehensive drone network service architecture tailored for secure and efficient operations of drones. This research paper addresses this gap by proposing a safe, reliable, and real-time drone network service architecture, emphasizing collaboration with fog computing. The contribution includes a systematic architecture design and integration of blockchain technology for secure data storage. Fog computing was introduced for the Drone with Blockchain Technology (FCDBT) model, where drones collaborate to process IoT data efficiently. The proposed algorithm dynamically plans drone trajectories and optimizes computation offloading. Results from simulations demonstrate the effectiveness of the proposed architecture, showcasing reduced average response latency and improved throughput, particularly when accessing resources from fog nodes. Furthermore, the model evaluates blockchain consensus algorithms (PoW, PoS, DAG) and recommends DAG for superior performance in handling IoT data. Fog; Drones; Blockchain; PSO; IoT; Vehicular.
无人机的性能，特别是对于时间敏感型任务而言，在各种应用中都至关重要。战略性地放置在物联网设备附近的雾节点充当无人机的计算资源，确保对有截止期限要求的任务能快速做出服务响应。然而，无人机有限的电池容量带来了挑战，这就需要节能的无人机物联网（IoD）系统。尽管对无人机飞行自动化的需求不断增加，但目前明显缺乏一个专门为无人机的安全高效运行量身定制的全面无人机网络服务架构。本研究论文通过提出一种安全、可靠且实时的无人机网络服务架构来填补这一空白，强调与雾计算的协作。其贡献包括系统的架构设计以及用于安全数据存储的区块链技术集成。为带有区块链技术的无人机（FCDBT）模型引入了雾计算，其中无人机协作以高效处理物联网数据。所提出的算法动态规划无人机轨迹并优化计算卸载。仿真结果证明了所提出架构的有效性，显示出平均响应延迟降低且吞吐量提高，特别是在从雾节点访问资源时。此外，该模型评估了区块链共识算法（工作量证明、权益证明、有向无环图），并推荐有向无环图在处理物联网数据方面具有卓越性能。雾；无人机；区块链；粒子群优化算法；物联网；车辆。
