Intern
Chair of Computer Science II - Software Engineering

Publications

Journal and Magazine Articles

  • The State of Serverless A...
    The State of Serverless Applications: Collection, Characterization, and Community Consensus. Eismann, Simon; Scheuner, Joel; van Eyk, Erwin; Schwinger, Maximilian; Grohmann, Johannes; Herbst, Nikolas; Abad, Cristina; Iosup, Alexandru; in Transactions on Software Engineering (2022). 48(10) 4152–4166.
  • SARDE: A Framework for Co...
    SARDE: A Framework for Continuous and Self-Adaptive Resource Demand Estimation. Grohmann, Johannes; Eismann, Simon; Bauer, Andr{é}; Spinner, Simon; Blum, Johannes; Herbst, Nikolas; Kounev, Samuel; in ACM Transactions on Autonomous and Adaptive Systems (2021). 15(2) Association for Computing Machinery, New York, NY, USA.
  • Serverless Applications:W...
    Serverless Applications:Why, When, and How?. Eismann, Simon; Joel, Scheuner; van Eyk, Erwin; Schwinger, Maximilian; Grohmann, Johannes; Herbst, Nikolas; Abad, Cristina; Iosup, Alexandru; in IEEE Software (2021). 38(1) 32–39.
  • A Taxonomy of Techniques ...
    A Taxonomy of Techniques for SLO Failure Prediction in Software Systems. Grohmann, Johannes; Herbst, Nikolas; Chalbani, Avi; Arian, Yair; Peretz, Noam; Kounev, Samuel; in Computers (2020). 9(1) 10. Multidisciplinary Digital Publishing Institute (MDPI).
  • The SPEC-RG Reference Arc...
    The SPEC-RG Reference Architecture for FaaS: From Microservices and Containers to Serverless Platforms. van Eyk, Erwin; Grohmann, Johannes; Eismann, Simon; Bauer, Andr{é}; Versluis, Laurens; Toader, Lucian; Schmitt, Norbert; Herbst, Nikolas; Abad, Cristina L.; Iosup, Alexandru; in IEEE Internet Computing (2019). 23(6) 7–18. IEEE.
  • Online model learning for...
    Online model learning for self-aware computing infrastructures. Spinner, Simon; Grohmann, Johannes; Eismann, Simon; Kounev, Samuel; in Journal of Systems and Software (2019). 147 1–16.

Full Conference Papers

  • Why Is It Not Solved Yet?...
    Why Is It Not Solved Yet? Challenges for Production-Ready Autoscaling. Straesser, Martin; Grohmann, Johannes; von Kistowski, J{ó}akim; Eismann, Simon; Bauer, Andr{é}; Kounev, Samuel; in Proceedings of the 2022 ACM/SPEC on International Conference on Performance Engineering (2022). 105–115. Association for Computing Machinery, New York, NY, USA.
  • {Investigating the Predictability of QoS Metrics in Cellular Networks}. Herrnleben, Stefan; Grohmann, Johannes; Lesch, Veronika; Prantl, Thomas; Metzger, Florian; Hoßfeld, Tobias; Kounev, Samuel; in 2022 IEEE/ACM 30th International Symposium on Quality of Service (IWQoS) (2022). 1–10.
  • A Simulation-based Optimi...
    A Simulation-based Optimization Framework for Online Adaptation of Networks. Herrnleben, Stefan; Grohmann, Johannes; Rygielski, Pitor; Lesch, Veronika; Krupitzer, Christian; Kounev, Samuel; in Proceedings of the 12th EAI International Conference on Simulation Tools and Techniques (SIMUtools), H. Song, D. Jiang (eds.) (2021). 513–532. Springer International Publishing, Cham.
  • A Predictive Maintenance ...
    A Predictive Maintenance Methodology: Predicting the Time-to-Failure of Machines in Industry 4.0. Züfle, Marwin; Agne, Joachim; Grohmann, Johannes; Dörtoluk, Ibrahim; Kounev, Samuel; in Proceedings of the 21st IEEE IES International Conference on Industrial Informatics (2021). IEEE.
  • SuanMing: Explainable Pre...
    SuanMing: Explainable Prediction of Performance Degradations in Microservice Applications. Grohmann, Johannes; Straesser, Martin; Chalbani, Avi; Eismann, Simon; Arian, Yair; Herbst, Nikolas; Peretz, Noam; Kounev, Samuel; in Proceedings of the 12th ACM/SPEC International Conference on Performance Engineering (ICPE) (2021). ACM, New York, NY, USA.
    Acceptance Rate: 29%
  • Libra: A Benchmark for Ti...
    Libra: A Benchmark for Time Series Forecasting Methods. Bauer, Andr{é}; Z{ü}fle, Marwin; Eismann, Simon; Grohmann, Johannes; Herbst, Nikolas; Kounev, Samuel; in Proceedings of the 12th ACM/SPEC International Conference on Performance Engineering (ICPE) (2021). ACM, New York, NY, USA.
  • Sizeless: Predicting the ...
    Sizeless: Predicting the Optimal Size of Serverless Functions. Eismann, Simon; Bui, Long; Grohmann, Johannes; Abad, Cristina; Herbst, Nikolas; Kounev, Samuel; in Proceedings of the 22nd International MIDDLEWARE Conference (2021). 248–259.
    Best Student Paper Award, ACM Artifacts Evaluated — Functional
  • ComBench: A Benchmarking...
    ComBench: A Benchmarking Framework for Publish/Subscribe Communication Protocols Under Network Limitations. Herrnleben, Stefan; Leidinger, Maximilian; Lesch, Veronika; Prantl, Thomas; Grohmann, Johannes; Krupitzer, Christian; Kounev, Samuel; in Performance Evaluation Methodologies and Tools, Q. Zhao, L. Xia (eds.) (2021). 72–92. Springer International Publishing, Cham.
  • Baloo: Measuring and Mode...
    Baloo: Measuring and Modeling the Performance Configurations of Distributed DBMS. Grohmann, Johannes; Seybold, Daniel; Eismann, Simon; Leznik, Mark; Kounev, Samuel; Domaschka, Jörg; in 2020 28th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS) (2020). 1–8. IEEE.
    Acceptance Rate: 27%
  • An IoT Network Emulator f...
    An IoT Network Emulator for Analyzing the Influence of Varying Network Quality. Herrnleben, Stefan; Ailabouni, Rudy; Grohmann, Johannes; Prantl, Thomas; Krupitzer, Christian; Kounev, Samuel; in Proceedings of the 12th EAI International Conference on Simulation Tools and Techniques (SIMUtools) (2020).
  • Predicting the Costs of S...
    Predicting the Costs of Serverless Workflows. Eismann, Simon; Grohmann, Johannes; van Eyk, Erwin; Herbst, Nikolas; Kounev, Samuel; in Proceedings of the 2020 ACM/SPEC International Conference on Performance Engineering (ICPE) (2020). 265–276. Association for Computing Machinery (ACM), New York, NY, USA.
    {Acceptance Rate: 23.4% (15/64)}
  • Incremental Calibration o...
    Incremental Calibration of Architectural Performance Models with Parametric Dependencies. Mazkatli, Manar; Monschein, David; Grohmann, Johannes; Koziolek, Anne; in 2020 IEEE International Conference on Software Architecture (ICSA 2020) (2020). 23–34. IEEE.
  • {To Fail Or Not To Fail: ...
    {To Fail Or Not To Fail: Predicting Hard Disk Drive Failure Time Windows}. Z{ü}fle, Marwin; Krupitzer, Christian; Erhard, Florian; Grohmann, Johannes; Kounev, Samuel; in Proceedings of the 20th International GI/ITG Conference on Measurement, Modelling and Evaluation of Computing Systems (2020). 19–36. Springer, Cham.
  • {Model-based Performance ...
    {Model-based Performance Predictions for SDN-based Networks: A Case Study}. Herrnleben, Stefan; Rygielski, Piotr; Grohmann, Johannes; Eismann, Simon; Hossfeld, Tobias; Kounev, Samuel; in Proceedings of the 20th International GI/ITG Conference on Measurement, Modelling and Evaluation of Computing Systems (2020). Springer, Cham.
  • {Detecting Parametric Dep...
    {Detecting Parametric Dependencies for Performance Models Using Feature Selection Techniques}. Grohmann, Johannes; Eismann, Simon; Elflein, Sven; Mazkatli, Manar; von Kistowski, J{ó}akim; Kounev, Samuel; in 2019 IEEE 27th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS) (2019). 309–322. IEEE Computer Society.
    {Acceptance Rate: 23.8% (29/122)}
  • On Learning in Collective...
    On Learning in Collective Self-Adaptive Systems: State of Practice and a 3D Framework. {D’Angelo}, M.; {Gerasimou}, S.; {Ghahremani}, S.; {Grohmann}, J.; {Nunes}, I.; {Pournaras}, E.; {Tomforde}, S.; in Proceedings of the 14th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (2019). 13–24. IEEE Press.
  • {Integrating Statistical ...
    {Integrating Statistical Response Time Models in Architectural Performance Models}. Eismann, Simon; Grohmann, Johannes; Walter, J{ü}rgen; von Kistowski, J{ó}akim; Kounev, Samuel; in Proceedings of the 2019 IEEE International Conference on Software Architecture (ICSA) (2019). 71–80. IEEE.
    Acceptance Rate: 21,9\% (21/96)
  • Monitorless: Predicting P...
    Monitorless: Predicting Performance Degradation in Cloud Applications with Machine Learning. Grohmann, Johannes; Nicholson, Patrick K.; Iglesias, Jesus Omana; Kounev, Samuel; Lugones, Diego; in Proceedings of the 20th International Middleware Conference (2019). 149–162. Association for Computing Machinery (ACM), New York, NY, USA.
  • {Predicting Server Power ...
    {Predicting Server Power Consumption from Standard Rating Results}. von Kistowski, J{ó}akim; Grohmann, Johannes; Schmitt, Norbert; Kounev, Samuel; in Proceedings of the 19th ACM/SPEC International Conference on Performance Engineering (2019). 301–312. Association for Computing Machinery (ACM), New York, NY, USA.
    {Full Paper Acceptance Rate: 18.6\% (13/70)}
  • {TeaStore: A Micro-Servic...
    {TeaStore: A Micro-Service Reference Application for Benchmarking, Modeling and Resource Management Research}. von Kistowski, J{ó}akim; Eismann, Simon; Schmitt, Norbert; Bauer, Andr{é}; Grohmann, Johannes; Kounev, Samuel; in Proceedings of the 26th IEEE International Symposium on the Modelling, Analysis, and Simulation of Computer and Telecommunication Systems (2018). 223–236. IEEE Computer Society.
    {Acceptance Rate: 29.5\% (23/78)}
  • {On the Value of Service ...
    {On the Value of Service Demand Estimation for Auto-Scaling}. Bauer, Andr{é}; Grohmann, Johannes; Herbst, Nikolas; Kounev, Samuel; in Proceedings of 19th International GI/ITG Conference on Measurement, Modelling and Evaluation of Computing Systems (MMB 2018) (2018). (Vol. 10740) 142–156. Springer, Cham.

Short Conference Papers

  • Same, Same, but Dissimila...
    Same, Same, but Dissimilar: Exploring Measurements for Workload Time-Series Similarity. Leznik, Mark; Grohmann, Johannes; Kliche, Nina; Bauer, Andr{é}; Seybold, Daniel; Eismann, Simon; Kounev, Samuel; Domaschka, J{ö}rg; in Proceedings of the 2022 ACM/SPEC on International Conference on Performance Engineering (2022). 89–96. Association for Computing Machinery, New York, NY, USA.
  • {An Automated Forecasting...
    {An Automated Forecasting Framework based on Method Recommendation for Seasonal Time Series}. Bauer, Andr{é}; Z{ü}fle, Marwin; Grohmann, Johannes; Schmitt, Norbert; Herbst, Nikolas; Kounev, Samuel; in Proceedings of the ACM/SPEC International Conference on Performance Engineering (2020). 48–55. Association for Computing Machinery (ACM), New York, NY, USA.
  • {How is Performance Addre...
    {How is Performance Addressed in DevOps?}. Bezemer, Cor{-}Paul; Eismann, Simon; Ferme, Vincenzo; Grohmann, Johannes; Heinrich, Robert; Jamshidi, Pooyan; Shang, Weiyi; van Hoorn, Andr{{é}}; Villavicencio, M{{ó}}nica; Walter, J{{ü}}rgen; Willnecker, Felix; in Proceedings of the 2019 ACM/SPEC International Conference on Performance Engineering (2019). 45–50. Association for Computing Machinery (ACM), New York, NY, USA.
  • {Self-Tuning Resource Dem...
    {Self-Tuning Resource Demand Estimation}. Grohmann, Johannes; Herbst, Nikolas; Spinner, Simon; Kounev, Samuel; in Proceedings of the 14th IEEE International Conference on Autonomic Computing (ICAC 2017) (2017). 21–26.

Workshop Papers

  • Optimizing Parametric Dep...
    Optimizing Parametric Dependencies for Incremental Performance Model Extraction. Voneva, Sonya; Mazkatli, Manar; Grohmann, Johannes; Koziolek, Anne; in Companion of the 14th European Conference Software Architecture ({ECSA} 2020), H. Muccini, P. Avgeriou, B. Buhnova, J. C{{á}}mara, M. Caporuscio, M. Franzago, A. Koziolek, P. Scandurra, C. Trubiani, D. Weyns, U. Zdun (eds.) (2020). (Vol. 1269) 228–240. Springer, Cham.
  • Learning to Learn in Coll...
    Learning to Learn in Collective Adaptive Systems: Mining Design Pattern for Data-driven Reasoning. D’Angelo, Mirko; Ghahremani, Sona; Gerasimou, Simos; Grohmann, Johannes; Nunes, Ingrid; Tomforde, Sven; Pournaras, Evangelos; in 2020 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C) (2020). 121–126. IEEE.
  • {On Learning Parametric D...
    {On Learning Parametric Dependencies from Monitoring Data}. Grohmann, Johannes; Eismann, Simon; Kounev, Samuel; in Proceedings of the 10th Symposium on Software Performance 2019 (SSP’19) (2019).
  • {Systematic Search for Op...
    {Systematic Search for Optimal Resource Configurations of Distributed Applications}. Bauer, Andr{é}; Eismann, Simon; Grohmann, Johannes; Herbst, Nikolas; Kounev, Samuel; in 2019 IEEE 4th International Workshops on Foundations and Applications of Self* Systems (FAS*W) (2019). 120–125. IEEE Computer Society, Los Alamitos, CA, USA.
  • {Utilizing Clustering to ...
    {Utilizing Clustering to Optimize Resource Demand Estimation Approaches}. Grohmann, Johannes; Eismann, Simon; Bauer, Andre; Zuefle, Marwin; Herbst, Nikolas; Kounev, Samuel; in 2019 IEEE 4th International Workshops on Foundations and Applications of Self* Systems (FAS*W) (2019). 134–139. IEEE.
  • Black-box Learning of Par...
    Black-box Learning of Parametric Dependencies for Performance Models. Ackermann, Vanessa; Grohmann, Johannes; Eismann, Simon; Kounev, Samuel; in Proceedings of 13th International Workshop on Models@run.time (MRT), co-located with ACM/IEEE 21st International Conference on Model Driven Engineering Languages and Systems (MODELS 2018) (2018).

Vision, Position, Demo, and Poster Papers

  • Buzzy: Towards Realistic ...
    Buzzy: Towards Realistic DBMS Benchmarking via Tailored, Representative, Synthetic Workloads. Domaschka, Jörg; Eismann, Simon; Leznik, Mark; Grohmann, Johannes; Kounev, Samuel; Seybold, Daniel; in Companion of the ACM/SPEC International Conference on Performance Engineering (2021). (Vol. ICPE ’21) 175–178. Association for Computing Machinery, New York, NY, USA.
  • TeaStore: A Micro-Service...
    TeaStore: A Micro-Service Reference Application for Cloud Researchers. Eismann, Simon; v. Kistowski, J{ó}akim; Grohmann, Johannes; Bauer, Andr{é}; Schmitt, Norbert; Herbst, Nikolas; Kounev, Samuel; in Proceedings of 2018 IEEE/ACM International Conference on Utility and Cloud Computing Companion (UCC Companion) (2018). 11–12. IEEE.
  • {The Vision of Self-Aware...
    {The Vision of Self-Aware Performance Models}. Grohmann, Johannes; Eismann, Simon; Kounev, Samuel; in 2018 IEEE International Conference on Software Architecture Companion (ICSA-C) (2018). 60–63.
  • Using Machine Learning fo...
    Using Machine Learning for Recommending Service Demand Estimation Approaches. Grohmann, Johannes; Herbst, Nikolas; Spinner, Simon; Kounev, Samuel; in Proceedings of the 8th International Conference on Cloud Computing and Services Science (CLOSER 2018) (2018). 473–480. SciTePress.
  • {Tools for Declarative Pe...
    {Tools for Declarative Performance Engineering}. Walter, J{ü}rgen; Eismann, Simon; Grohmann, Johannes; Okanovic, Dusan; Kounev, Samuel; in Companion of the 2018 ACM/SPEC International Conference on Performance Engineering (2018). 53–56. Association for Computing Machinery (ACM), New York, NY, USA.
  • A {SPEC RG} Cloud Group's...
    A {SPEC RG} Cloud Group’s Vision on the Performance Challenges of FaaS Cloud Architectures. van Eyk, Erwin; Iosup, Alexandru; Abad, Cristina L.; Grohmann, Johannes; Eismann, Simon; in Companion of the 2018 ACM/SPEC International Conference on Performance Engineering (2018). 21–24. Association for Computing Machinery (ACM), New York, NY, USA.

Dissertation

  • Model Learning for Perfor...
    Model Learning for Performance Prediction of Cloud-native Microservice Applications. Grohmann, Johannes; (2022, March). Universität Würzburg.
    Distinction

Techreports

  • A Review of Serverless Us...
    A Review of Serverless Use Cases and their Characteristics Eismann, Simon; Scheuner, Joel; van Eyk, Erwin; Schwinger, Maximilian; Grohmann, Johannes; Herbst, Nikolas; Abad, Cristina; Iosup, Alexandru; (2020). SPEC RG.