Cumulus:一个用于边缘云计算卸载的分布式和灵活的计算测试平台

Hend K. Gedawy, Sannan Tariq, Abderrahmen Mtibaa, Khaled A. Harras
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引用次数: 32

摘要

虽然智能设备的数量、计算资源和通信能力都在不断增加,但当前的应用程序需求往往超过了硬件的改进。最近,有人提出将计算卸载到远程云资源或位置较近的计算资源,如cloudlets或其他移动设备和物联网设备。在本文中,我们提出了“Cumulus”,一个边缘云计算卸载的开源平台。Cumulus旨在帮助工程师和研究人员构建、测试和评估他们的边缘计算应用程序、调度方法等。我们提出了一个通用的、灵活的Cumulus架构,以及一个利用大量异构设备、通信方法和操作系统的概念验证测试平台原型。测试平台由独立的工作物联网设备和物联网设备的集群边缘移动云组成。我们通过可视化工具增强了Cumulus,该工具可以实时监控在测试台上运行的设备所使用的资源。我们通过在不同设置下演示几种卸载算法下的性能来评估行动中的Cumulus。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cumulus: A distributed and flexible computing testbed for edge cloud computational offloading
While smart devices are increasing in numbers, compute resources, and communication capabilities, current application requirements are often outpacing such hardware improvement. Recently, offloading computation to remote cloud resources or closely located computing resources, such as cloudlets or other mobile and IoT devices have been proposed. In this paper, we propose “Cumulus”, an open source platform for edge cloud computational offloading. Cumulus aims at helping engineers and researchers build, test, and evaluate their edge-computing applications, scheduling methods, etc. We present a generic and flexible architecture of Cumulus as well as a proof-of-concept testbed prototype leveraging a large spectrum of heterogeneous devices, communication methods, and OSs. The testbed consists of standalone worker IoT devices and clustered edge mobile clouds of IoT devices. We enhance Cumulus with a visualization tool that allows real time monitoring of resources used by the devices running on the testbed. We evaluate Cumulus in action by demonstrating its performance under several offloading algorithms in different settings.
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