用于基准测试的边缘工作负载跟踪收集和分析

Klervie Toczé, Norbert Schmitt, Ulf Kargén, Atakan Aral, I. Brandić
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引用次数: 2

摘要

边缘计算这一新兴领域正面临缺乏代表性数据来评估快速引入的新算法或技术的问题。这是一个关键问题,因为这个复杂的范例有许多不同的用例,这些用例转化为高度多样化的工作负载类型集。在这项工作中,在SPEC RG Cloud的边缘计算活动的背景下,我们继续通过定义高级工作负载类以及收集和分析三个现实世界边缘应用程序的踪迹来实现边缘基准,根据现有文献,这些应用程序是这些类的代表。此外,我们提出了一种实用的、通用的工作负载定义和收集方法。跟踪和收集工具是开源的。在对收集的工作负载的分析中,我们发现了文献和获得的跟踪之间的差异,因此强调了需要继续努力收集和提供来自实际应用程序的数据,这可以使用建议的跟踪收集方法来完成。此外,我们还讨论了通过我们的分析浮出水面的各种见解和未来方向。
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Edge Workload Trace Gathering and Analysis for Benchmarking
The emerging field of edge computing is suffering from a lack of representative data to evaluate rapidly introduced new algorithms or techniques. That is a critical issue as this complex paradigm has numerous different use cases which translate into a highly diverse set of workload types.In this work, within the context of the edge computing activity of SPEC RG Cloud, we continue working towards an edge benchmark by defining high-level workload classes as well as collecting and analyzing traces for three real-world edge applications, which, according to the existing literature, are the representatives of those classes. Moreover, we propose a practical and generic methodology for workload definition and gathering. The traces and gathering tool are provided open-source.In the analysis of the collected workloads, we detect discrepancies between the literature and the traces obtained, thus highlighting the need for a continuing effort into gathering and providing data from real applications, which can be done using the proposed trace gathering methodology. Additionally, we discuss various insights and future directions that rise to the surface through our analysis.
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