Edge Workload Trace Gathering and Analysis for Benchmarking

Edge Workload Trace Gathering and Analysis for Benchmarking

Abstract

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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Authors
  • Toczé, Klervie
  • Schmitt, Norbert
  • Kargén, Ulf
  • Aral, Atakan
  • Brandić, Ivona
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Projects
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Shortfacts
Category
Paper in Conference Proceedings or in Workshop Proceedings (Paper)
Event Title
6th IEEE International Conference on Fog and Edge Computing 2022
Divisions
Scientific Computing
Subjects
Datenverarbeitungsmanagement
Systemarchitektur Allgemeines
Event Location
Messina, Italy
Event Type
Conference
Event Dates
16.05.2022
Date
16 May 2022
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