Low AoI Multi-UAV IoT Task Allocation and Trajectory Planning
Age of information(AoI)provides an accurate measure of the value of data.In order to minimize average Aol in emergency Internet of things(IoT)communication,unmanned aerial vehicle(UAV)is introduced as an information relay,and a task assignment and trajectory optimization algorithm based on a deep reinforcement learning framework is proposed.Firstly,by analyzing the relationship between AoI minimization problem and the UAV,it is solved in two stages.Secondly,the k-meanis++clustering algorithm is used to assign tasks to the UAV,and the trajectory of the UAV is optimized in real-time through the pointer network according to the flight distance,disaster situation and rescue team needs.Finally,a centralized information-sharing mechanism is designed to save energy consumption and information distribution time.The experimental results show that compared with traditional methods,the proposed optimization algorithm can achieve a smaller AoI in the UAV emergency disaster relief,thus alleviating the temporary communication pressure caused by emergency disaster relief.
unmanned aerial vehicle-assisted Internet of thingsage of informationtask assignmenttrajectory optimizationdeep reinforcement learning
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