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Johannes Grohmann

Publication record assembled from the DBLP archive of ranked conferences.

Papers indexed

15

Venues

10

Active years

2018–2022

Best venue rank

A*

Where they publish

Papers

15 indexed papers, newest first.

YearVenueTitleAuthors
2022IWQoSInvestigating the Predictability of QoS Metrics in Cellular Networks.Stefan Herrnleben, Johannes Grohmann, Veronika Lesch, Thomas Prantl, Florian Metzger, Tobias Hofeld, Samuel Kounev
2021INDINA Predictive Maintenance Methodology: Predicting the Time-to-Failure of Machines in Industry 4.0.Marwin Zfle, Joachim Agne, Johannes Grohmann, Ibrahim Drtoluk, Samuel Kounev
2021MiddlewareSizeless: predicting the optimal size of serverless functions.Simon Eismann, Long Bui, Johannes Grohmann, Cristina L. Abad, Nikolas Herbst, Samuel Kounev
2020ECSAOptimizing Parametric Dependencies for Incremental Performance Model Extraction.Sonya Voneva, Manar Mazkatli, Johannes Grohmann, Anne Koziolek
2020ICSAIncremental Calibration of Architectural Performance Models with Parametric Dependencies.Manar Mazkatli, David Monschein, Johannes Grohmann, Anne Koziolek
2020MASCOTSBaloo: Measuring and Modeling the Performance Configurations of Distributed DBMS.Johannes Grohmann, Daniel Seybold, Simon Eismann, Mark Leznik, Samuel Kounev, Jrg Domaschka
2019ICSAIntegrating Statistical Response Time Models in Architectural Performance Models.Simon Eismann, Johannes Grohmann, Jrgen Walter, Jakim von Kistowski, Samuel Kounev
2019ICSEOn learning in collective self-adaptive systems: state of practice and a 3D framework.Mirko D'Angelo, Simos Gerasimou, Sona Ghahremani, Johannes Grohmann, Ingrid Nunes, Evangelos Pournaras, Sven Tomforde
2019MASCOTSDetecting Parametric Dependencies for Performance Models Using Feature Selection Techniques.Johannes Grohmann, Simon Eismann, Sven Elflein, Jakim von Kistowski, Samuel Kounev, Manar Mazkatli
2019MiddlewareMonitorless: Predicting Performance Degradation in Cloud Applications with Machine Learning.Johannes Grohmann, Patrick K. Nicholson, Jesus Omaa Iglesias, Samuel Kounev, Diego Lugones
2018CLOSERUsing Machine Learning for Recommending Service Demand Estimation Approaches - Position Paper.Johannes Grohmann, Nikolas Herbst, Simon Spinner, Samuel Kounev
2018ICSAThe Vision of Self-Aware Performance Models.Johannes Grohmann, Simon Eismann, Samuel Kounev
2018MASCOTSTeaStore: A Micro-Service Reference Application for Benchmarking, Modeling and Resource Management Research.Jakim von Kistowski, Simon Eismann, Norbert Schmitt, Andr Bauer, Johannes Grohmann, Samuel Kounev
2018MODELSBlackbox Learning of Parametric Dependencies for Performance Models.Vanessa Ackermann, Johannes Grohmann, Simon Eismann, Samuel Kounev
2018UCCTeaStore: A Micro-Service Reference Application for Cloud Researchers.Simon Eismann, Jakim von Kistowski, Johannes Grohmann, Andr Bauer, Norbert Schmitt, Nikolas Herbst, Samuel Kounev