An aggregate flow based scheduler in multi-task cooperated UAVs network

Unmanned Aerial Vehicles (UAVs) cooperative multi-task system has become the research focus in recent years. However, the existing network frameworks of UAVs are not flexible and efficient enough to deal with the complex multi-task scheduling, because they are not able to perceive the different features. In this paper, a novel cooperated UAVs network framework for multi-task scheduling is proposed. It is a three-layer network including a core layer, an aggregation layer and an execution layer, which enhances the efficiency of multi-task distribution, aggregation and transmission. Furthermore, an AggreGate Flow (AGFlow) based scheduler is dedicatedly designed to maximize the task completion rate, whose key point is to aggregate flows belonging to one task during the multi-task transmission of UAVs network and to allocate priority by calculating the urgency-level of each AGFlow. Simulation results demonstrate that, compared with that of state-of-the-art scheduler, the average task completion rate of AGFlow based scheduler is raised by 0.278.