In this work, we study a hierarchical non-terrestrial network as an edge-cloud platform for remote computing of tasks generated by remote ad-hoc healthcare facility deployments, or internet of medical things (IoMT) devices. We consider a high altitude platform station (HAPS) to provide local multiaccess edge server (MEC) services to a set of remote ground medical devices, and a low-earth orbit (LEO) satellite, serving as a bridge to a remote cloud computing server through a ground gateway (GW), providing a large amount of computing resources to the HAPS. In this hierarchical system, the HAPS and the cloud server charges the ground users and the HAPS for the use of the spectrum and the computing of their tasks respectively. Each tier seeks to maximize their own utility in a selfish manner. To encourage the prompt computation of the tasks, a local delay cost is assumed. We formulate the optimal per-task cost at each tier that influences the corresponding offloading policies, and find the corresponding optimal bandwidth allocation.

翻译：本文研究了一种分层非地面网络，作为远程临时医疗设施部署或医疗物联网设备生成任务的边缘-云计算平台。我们考虑采用高空平台站为远程地面医疗设备提供本地多接入边缘计算服务，并利用低地球轨道卫星作为通过地面网关连接远程云计算服务器的桥梁，为高空平台站提供大规模计算资源。在此分层系统中，高空平台站与云服务器分别向地面用户和高空平台站收取频谱使用与任务计算费用。各层级均以自私方式追求自身效用最大化。为激励任务即时计算，系统引入了本地延迟成本。我们构建了影响各层级卸载策略的最优单任务成本模型，并求解出相应的最优带宽分配方案。