This paper investigates traffic flow modeling issue in multi-services oriented unmanned aerial vehicle (UAV)-enabled wireless networks, which is critical for supporting future various applications of such networks. We propose a general traffic flow model for multi-services oriented UAV-enable wireless networks. Under this model, we first classify the network services into three subsets: telemetry, Internet of Things (IoT), and streaming data. Based on the Pareto distribution, we then partition all UAVs into three subgroups with different network usage. We further determine the number of packets for different network services and total data size according to the packet arrival rate for the nine segments, each of which represents one map relationship between a subset of services and a subgroup of UAVs. Simulation results are provided to illustrate that the number of packets and the data size predicted by our traffic model can well match with these under a real scenario.
翻译:本文调查多服务型无人驾驶飞行器(无人驾驶飞行器)辅助无线网络的交通流量模型问题,这对支持此类网络今后的各种应用至关重要。我们为多服务型无人驾驶飞行器(无人驾驶飞行器)可使用的无线网络提出了一个通用交通流量模型。根据这一模型,我们首先将网络服务分为三个子群:遥测、物联网和流数据。根据Pareto分布,我们然后将所有无人驾驶飞行器分成三个子群,使用不同的网络。我们进一步根据9个部分的组合抵达率确定不同网络服务的包件数量和总数据大小,每个部分代表一组服务与无人驾驶飞行器分组之间的一个地图关系。提供了模拟结果,以说明在真实情况下,我们的交通模式预测的包件数量和数据大小可以与这些数据相匹配。