Towards a Mobile App Platform for Personalized UAV Fleets using Edge and Cloud

Suman Raj, Yogesh L. Simmhan
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引用次数: 1

Abstract

Advances in edge computing, accelerators, computer vision, and artificial intelligence have led to the widespread application of autonomous vehicles such as drones. Besides logistics and urban safety, drones can also be used for social good. In this paper, we present the outline for a lightweight mobile app platform that can be used by the visually impaired for navigational assistance. The platform uses an intelligent middleware scheduler to perform DNN inferencing either on the onboard edge device or offloads it to a FaaS running on the cloud, while maximizing utility and the tasks processed. We validate our platform for multiple workloads, supporting up to 4 drones per edge device, with 7 edges running concurrently and using AWS Lambda as the remote cloud. We also test our platform using Jetson Nano and Tello drones as hardware validation.
利用边缘和云技术打造个性化无人机队移动应用平台
边缘计算、加速器、计算机视觉和人工智能方面的进步促使无人机等自动驾驶车辆得到广泛应用。除了物流和城市安全,无人机还可用于社会公益。在本文中,我们介绍了一个轻量级移动应用平台的概要,该平台可用于视障人士的导航辅助。该平台使用智能中间件调度器在机载边缘设备上执行 DNN 推断,或将其卸载到云上运行的 FaaS,同时最大限度地提高效用和处理的任务。我们针对多种工作负载验证了我们的平台,每个边缘设备最多支持 4 架无人机,7 个边缘设备同时运行,并使用 AWS Lambda 作为远程云。作为硬件验证,我们还使用 Jetson Nano 和 Tello 无人机测试了我们的平台。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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