Edge computing facilitates low-latency services at the network's edge by distributing computation, communication, and storage resources within the geographic proximity of mobile and Internet-of-Things (IoT) devices. The recent advancement in Unmanned Aerial Vehicles (UAVs) technologies has opened new opportunities for edge computing in military operations, disaster response, or remote areas where traditional terrestrial networks are limited or unavailable. In such environments, UAVs can be deployed as aerial edge servers or relays to facilitate edge computing services. This form of computing is also known as UAV-enabled Edge Computing (UEC), which offers several unique benefits such as mobility, line-of-sight, flexibility, computational capability, and cost-efficiency. However, the resources on UAVs, edge servers, and IoT devices are typically very limited in the context of UEC. Efficient resource management is, therefore, a critical research challenge in UEC. In this article, we present a survey on the existing research in UEC from the resource management perspective. We identify a conceptual architecture, different types of collaborations, wireless communication models, research directions, key techniques and performance indicators for resource management in UEC. We also present a taxonomy of resource management in UEC. Finally, we identify and discuss some open research challenges that can stimulate future research directions for resource management in UEC.
翻译:最近无人驾驶航空飞行器(UAVs)技术的进步为在军事行动、灾害应对或传统地面网络有限或没有传统的地面网络的偏远地区进行边缘计算提供了新的机会。在这种环境中,无人驾驶航空飞行器可以作为空中边缘服务器或中继器部署,以便利边缘计算服务。这种形式的计算也被称为UAV驱动的Edge Edge 计算(UEC),它提供一些独特的好处,如机动性、视觉线、灵活性、计算能力和成本效益。然而,无人驾驶航空飞行器、边缘服务器和IoT装置的资源在UEC中通常非常有限。因此,高效资源管理是UEC的一个关键研究挑战。在文章中,我们从资源管理的角度介绍了对UEC现有研究的调查。我们确定了一个概念架构、不同类型的协作、无线通信模型、研究方向、关键技术以及未来UEEC资源管理的业绩指标。我们还可以在UEC的当前税收资源管理中,为UEC的当前资源动态资源管理确定一个研究方向。