Fog computing is an emerging computing paradigm that uses processing and storage capabilities located at the edge, in the cloud, and possibly in between. Testing and benchmarking fog applications, however, is hard since runtime infrastructure will typically be in use or may not exist, yet. While approaches for the emulation of infrastructure testbeds do exist, their focus is typically the emulation of edge devices. Other approaches also emulate infrastructure within the core network or the cloud, but they miss support for automated experiment orchestration. In this paper, we propose to evaluate fog applications on an emulated infrastructure testbed created in the cloud which can be manipulated based on a pre-defined orchestration schedule. Developers can freely design the infrastructure, configure performance characteristics, manage application components, and orchestrate their experiments. We also present our proof-of-concept implementation MockFog 2.0. We use MockFog 2.0 to evaluate a fog-based smart factory application and showcase how its features can be used to study the impact of infrastructure changes and workload variations. With these experiments, we also show that MockFog can achieve good experiment reproducibility, even in a public cloud environment.
翻译:雾计算是一种新兴的计算模式,它使用位于边缘、云层和可能介于中间的加工和储存能力。 但是,测试和基准雾应用很困难,因为运行时的基础设施通常会使用或可能不存在。虽然模拟基础设施测试台的方法确实存在,但其重点通常是模拟边缘装置。其他方法也模仿核心网络或云层内部的基础设施,但它们却缺乏对自动实验管弦的支持。在本文中,我们提议评价云层中复制的基础设施测试台的雾应用,该测试台可以根据预先确定的调控时间表进行操纵。开发者可以自由设计基础设施,配置性能特征,管理应用程序组件,并安排他们的实验。我们还介绍了我们的测试原理实施MockFog 2. 0。我们用MockFog 2. 0 来评价一个基于雾的智能工厂应用程序,并展示其特征如何用于研究基础设施变化和工作量变化的影响。我们通过这些实验还表明,即便在公共云层环境中,MockFog也可以实现良好的实验再生能力。