In recent years, cloud and edge architectures have gained tremendous focus for offloading computationally heavy applications. From machine learning and Internet of Thing (IOT) to industrial procedures and robotics, cloud computing have been used extensively for data processing and storage purposes, thanks to its "infinite" resources. On the other hand, cloud computing is characterized by long time delays due to the long distance between the cloud servers and the machine requesting the resources. In contrast, edge computing provides almost real-time services since edge servers are located significantly closer to the source of data. This capability sets edge computing as an ideal option for real-time applications, like high level control, for resource-constrained platforms. In order to utilize the edge resources, several technologies, with basic ones as containers and orchestrators like Kubernetes, have been developed to provide an environment with many features, based on each application's requirements. In this context, this works presents the implementation and evaluation of a novel edge architecture based on Kubernetes orchestration for controlling the trajectory of a resource-constrained Unmanned Aerial Vehicle (UAV) by enabling Model Predictive Control (MPC).

翻译：近年来，云架构和边缘架构通过将计算密集型任务进行卸载，已受到广泛关注。从机器学习、物联网到工业流程和机器人领域，云计算因其“无限”资源而被广泛用于数据处理和存储。然而，云计算的特点在于云端服务器与请求资源的机器之间距离较长，导致较大的时间延迟。相比之下，边缘服务器紧邻数据源，能够提供近乎实时的服务，这使得边缘计算成为资源受限平台进行高级控制等实时应用的理想选择。为利用边缘资源，业界已开发了多种技术，其中基本技术包括容器和Kubernetes等编排器，它们能根据各应用需求提供具有丰富特性的运行环境。在此背景下，本文提出并评估了一种基于Kubernetes编排的新型边缘架构，通过启用模型预测控制，实现对资源受限无人机的轨迹控制。