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Towards Edge Benchmarking: A Methodology for Characterizing Edge Workloads
Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, Faculty of Science & Engineering. (Real-time Systems Laboratory)ORCID iD: 0000-0002-7300-3603
University of Würzburg; Germany.
Vienna University of Technology, Austria.
Vienna University of Technology, Austria.
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2019 (English)In: Proceedings of 4th International Workshop on Foundations and Applications of Self* Systems (FAS*W),, IEEE, 2019, p. 70-71Conference paper, Published paper (Refereed)
Abstract [en]

The edge computing paradigm has recently attracted research efforts coming from different application domains. However, evaluating an edge platform or algorithm is impeded by the lack of suitable benchmarks. We propose a methodology for characterizing edge workloads from different application domains. It is a first step towards defining workloads to be included in a future edge benchmarking suite. We evaluate the methodology on three use cases and find that defining a common and standard set of workloads is plausible.

Place, publisher, year, edition, pages
IEEE, 2019. p. 70-71
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:liu:diva-161760DOI: 10.1109/FAS-W.2019.00030ISI: 000518905900017Scopus ID: 2-s2.0-85071474510ISBN: 978-1-7281-2406-3 (electronic)OAI: oai:DiVA.org:liu-161760DiVA, id: diva2:1368920
Conference
4th International Workshop on Foundations and Applications of Self* Systems (FAS*W), Umea, Sweden, 16-20 June 2019
Note

Funding agencies:  Swedish national graduate school in computer science (CUGS)

Available from: 2019-11-08 Created: 2019-11-08 Last updated: 2020-03-29Bibliographically approved

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Toczé, KlervieNadjm-Tehrani, Simin

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CiteExportLink to record
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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
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