The invention relates to a service resource allocation method for an unmanned aerial vehicle assisted wireless charging edge intelligent system, and the method comprises the steps: building a bipartite graph, solving a minimum unmanned aerial vehicle flight total time problem of task execution through a K-M algorithm, and allocating flight tasks of all unmanned aerial vehicles according to an optimal allocation decision vector g *; and for the unmanned aerial vehicle arriving at the task area, obtaining an unloading decision vector of each device in a single task area through a trained deep learning neural network DNN in a time frame-by-frame manner. And calculating a feasible region range of the wireless charging time of the unmanned aerial vehicle based on the unloading decision vector, distributing the wireless charging time calculated by the feasible decision vector to the unmanned aerial vehicle, and executing an online unloading task between the unmanned aerial vehicle and each device according to the decision vector.
本发明涉及一种面向无人机辅助无线充电边缘智能系统的服务资源分配方法,包括:建立二分图以K‑M算法求解执行任务的最小无人机飞行总时间问题,根据最佳分配决策向量g*,分配各无人机的飞行任务;对到达任务区域的无人机逐时间帧地,通过向一训练好的深度学习神经网络DNN得到单个任务区域内各设备的卸载决策向量。基于卸载决策向量计算无人机无线充电时间的可行域范围,将可行的决策向量所计算无线充电时间分配给无人机并依照决策向量在无人机与各设备间执行在线卸载任务。
Service resource allocation method for unmanned aerial vehicle assisted wireless charging edge intelligence system
面向无人机辅助无线充电边缘智能系统的服务资源分配方法
16.04.2024
Patent
Elektronische Ressource
Chinesisch
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