论文标题
6G中的无人机/HAP辅助车辆边缘计算：在哪里和什么要卸载？
UAV/HAP-Assisted Vehicular Edge Computing in 6G: Where and What to Offload?
论文作者
论文摘要
在第六代（6G）网络的背景下，车辆边缘计算（VEC）正在成为一种有前途的解决方案，可以使电池供电的地面车辆具有有限的计算和存储资源，将处理任务卸载到更强大的设备上。鉴于动态的车辆环境，VEC系统必须尽可能灵活，聪明和自适应。为此，在本文中，我们研究了通过非事物网络（NTNS）实现VEC的机会，在该网络中，地面车辆将渴望资源的任务卸载到无人驾驶飞机（无人机），高海拔平台（HAPS）或两者的组合。我们定义了一个优化问题，其中任务被建模为泊松到达过程，并应用排队理论以找到系统中的最佳卸载因子。数值结果表明，即使在密集的网络中，天线辅助VEC也是可行的，只要提供大容量的HAP/UAV平台。
In the context of 6th generation (6G) networks, vehicular edge computing (VEC) is emerging as a promising solution to let battery-powered ground vehicles with limited computing and storage resources offload processing tasks to more powerful devices. Given the dynamic vehicular environment, VEC systems need to be as flexible, intelligent, and adaptive as possible. To this aim, in this paper we study the opportunity to realize VEC via non-terrestrial networks (NTNs), where ground vehicles offload resource-hungry tasks to Unmanned Aerial Vehicles (UAVs), High Altitude Platforms (HAPs), or a combination of the two. We define an optimization problem in which tasks are modeled as a Poisson arrival process, and apply queuing theory to find the optimal offloading factor in the system. Numerical results show that aerial-assisted VEC is feasible even in dense networks, provided that high-capacity HAP/UAV platforms are available.
