基于新型组网的无人机巡检任务处理优化方案OA

Considering user mobility,especially in the scenario of unmanned aerial vehicle inspection,it is likely that task migration will occur due to the small service range of Multi-access Edge Computing(MEC)node.Task migration will increase task processing time delay and cost.To reduce the probability of task migration,a new MEC structure-MEC POOL is proposed.On this basis,a task processing benefit model of MEC POOL structure is constructed.The problem of optimal task processing benefit is converted into the problem of optimal solution under restricted conditions.In order to solve the above optimal solution problem,a particle swarm optimization algorithm based on task processing benefit optimization is designed.The experimental results show that the task processing benefit and task processing delay benefit of the MEC POOL scheme are improved by more than 10％compared to the traditional MEC scheme in the scenario of task migration.For multi-user scenario,the average task processing benefit is improved by more than 8％and the average task processing time delay is reduced by more than 10％.