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出 处:《理论数学》2024年第1期224-234,共11页Pure Mathematics
摘 要:无人机(Unmanned Aerial Vehicles, UAVs)越来越多地被用作移动边缘计算(Mobile Edge Computing, MEC)中的移动服务器,并被广泛地集成到现代物联网应用中。本文在现有研究的无人机路径规划中,引入考虑无人机的能量消耗和无人机之间的合作,并用于改善提供给终端用户的服务质量(Quality of Service, QoS)。通过加深考虑无人机在飞行过程中以及处理终端用户的能量消耗以及多无人机的协作能力,提出相应的模型改进,通过观察无人机的飞行路径,验证所提算法的有效性和低耗性,并证明无人机之间团队合作的有效性。实验结果表明,所提模型在合作时更能降低总体能耗,并增强模拟环境的真实性。Unmanned Aerial Vehicles (UAVs) are increasingly being utilized as mobile servers in Mobile Edge Computing (MEC) and widely integrated into modern Internet of Things (IoT) applications. In this paper, we introduce a novel approach to UAV path planning that considers both the energy con-sumption of UAVs and their collaboration, aiming to improve the Quality of Service (QoS) provided to end users. By incorporating the energy consumption during UAV flight and the collaborative capabilities of multiple UAVs, we propose model enhancements. The effectiveness and efficiency of the proposed algorithms are validated through the observation of UAV flight paths, demonstrating the effectiveness of team collaboration among UAVs. Experimental results show that the proposed model significantly reduces overall energy consumption when UAVs cooperate, while enhancing the realism of the simulated environment.
分 类 号:V27[航空宇航科学与技术—飞行器设计]
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