Privacy-Preserving Sharing of Data Analytics Runtime Metrics for Performance Modeling

Will, J., Scheinert, D., Zunzer, S., Bode, J., Kring, C. and Thamsen, L. (2024) Privacy-Preserving Sharing of Data Analytics Runtime Metrics for Performance Modeling. In: ICPE 2024: The 9th Workshop on Challenges in Performance Methods for Software Development (WOSP-C), London, UK, 7-11 May 2024, (Accepted for Publication)

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Item Type:Conference Proceedings
Additional Information:This work has been supported through a grant by the German Research Foundation (DFG) as “C5” (grant 506529034).
Keywords:Distributed dataflows, resource allocation, performance modeling, data sharing, data privacy.
Status:Accepted for Publication
Refereed:Yes
Glasgow Author(s) Enlighten ID:Thamsen, Dr Lauritz
Authors: Will, J., Scheinert, D., Zunzer, S., Bode, J., Kring, C., and Thamsen, L.
College/School:College of Science and Engineering > School of Computing Science

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