Johannes Grohmann

53 papers A 4B 12C 2Journal 13Unranked 21

Year	Rank	Type	Title / Venue / Authors
2022	B	`conf`	Investigating the Predictability of QoS Metrics in Cellular Networks. IWQoS Stefan Herrnleben, Johannes Grohmann, Veronika Lesch, Thomas Prantl, Florian Metzger, Tobias Hoßfeld, Samuel Kounev
2022	—	`—`	Model Learning for Performance Prediction of Cloud-native Microservice Applications. Johannes Grohmann
2022	B	`conf`	Same, Same, but Dissimilar: Exploring Measurements for Workload Time-series Similarity. ICPE Mark Leznik, Johannes Grohmann, Nina Kliche, André Bauer, Daniel Seybold, Simon Eismann, Samuel Kounev, Jörg Domaschka
2022	J	`jnl`	The State of Serverless Applications: Collection, Characterization, and Community Consensus. IEEE Trans. Software Eng. Simon Eismann, Joel Scheuner, Erwin Van Eyk, Maximilian Schwinger, Johannes Grohmann, Nikolas Herbst, Cristina L. Abad, Alexandru Iosup
2022	B	`conf`	Why Is It Not Solved Yet?: Challenges for Production-Ready Autoscaling. ICPE Martin Straesser, Johannes Grohmann, Jóakim von Kistowski, Simon Eismann, André Bauer, Samuel Kounev
2021	C	`conf`	A Predictive Maintenance Methodology: Predicting the Time-to-Failure of Machines in Industry 4.0. INDIN Marwin Züfle, Joachim Agne, Johannes Grohmann, Ibrahim Dörtoluk, Samuel Kounev
2021	—	`conf`	Buzzy: Towards Realistic DBMS Benchmarking via Tailored, Representative, Synthetic Workloads: Vision Paper. ICPE (Companion) Jörg Domaschka, Mark Leznik, Daniel Seybold, Simon Eismann, Johannes Grohmann, Samuel Kounev
2021	—	`conf`	ComBench: A Benchmarking Framework for Publish/Subscribe Communication Protocols Under Network Limitations. VALUETOOLS Stefan Herrnleben, Maximilian Leidinger, Veronika Lesch, Thomas Prantl, Johannes Grohmann, Christian Krupitzer, Samuel Kounev
2021	B	`conf`	Libra: A Benchmark for Time Series Forecasting Methods. ICPE André Bauer, Marwin Züfle, Simon Eismann, Johannes Grohmann, Nikolas Herbst, Samuel Kounev
2021	J	`jnl`	SARDE: A Framework for Continuous and Self-Adaptive Resource Demand Estimation. ACM Trans. Auton. Adapt. Syst. Johannes Grohmann, Simon Eismann, André Bauer, Simon Spinner, Johannes Blum, Nikolas Herbst, Samuel Kounev
2021	J	`jnl`	Serverless Applications: Why, When, and How? IEEE Softw. Simon Eismann, Joel Scheuner, Erwin Van Eyk, Maximilian Schwinger, Johannes Grohmann, Nikolas Herbst, Cristina L. Abad, Alexandru Iosup
2021	A	`conf`	Sizeless: predicting the optimal size of serverless functions. Middleware Simon Eismann, Long Bui, Johannes Grohmann, Cristina L. Abad, Nikolas Herbst, Samuel Kounev
2021	B	`conf`	SuanMing: Explainable Prediction of Performance Degradations in Microservice Applications. ICPE Johannes Grohmann, Martin Straesser, Avi Chalbani, Simon Eismann, Yair Arian, Nikolas Herbst, Noam Peretz, Samuel Kounev
2020	J	`jnl`	A Review of Serverless Use Cases and their Characteristics. CoRR Simon Eismann, Joel Scheuner, Erwin Van Eyk, Maximilian Schwinger, Johannes Grohmann, Nikolas Herbst, Cristina L. Abad, Alexandru Iosup
2020	—	`conf`	A Simulation-Based Optimization Framework for Online Adaptation of Networks. SimuTools (1) Stefan Herrnleben, Johannes Grohmann, Piotr Rygielski, Veronika Lesch, Christian Krupitzer, Samuel Kounev
2020	J	`jnl`	A Taxonomy of Techniques for SLO Failure Prediction in Software Systems. Comput. Johannes Grohmann, Nikolas Herbst, Avi Chalbani, Yair Arian, Noam Peretz, Samuel Kounev
2020	B	`conf`	An Automated Forecasting Framework based on Method Recommendation for Seasonal Time Series. ICPE André Bauer, Marwin Züfle, Johannes Grohmann, Norbert Schmitt, Nikolas Herbst, Samuel Kounev
2020	—	`conf`	An IoT Network Emulator for Analyzing the Influence of Varying Network Quality. SimuTools (2) Stefan Herrnleben, Rudy Ailabouni, Johannes Grohmann, Thomas Prantl, Christian Krupitzer, Samuel Kounev
2020	B	`conf`	Baloo: Measuring and Modeling the Performance Configurations of Distributed DBMS. MASCOTS Johannes Grohmann, Daniel Seybold, Simon Eismann, Mark Leznik, Samuel Kounev, Jörg Domaschka
2020	A	`conf`	Incremental Calibration of Architectural Performance Models with Parametric Dependencies. ICSA Manar Mazkatli, David Monschein, Johannes Grohmann, Anne Koziolek
2020	J	`jnl`	Incremental Calibration of Architectural Performance Models with Parametric Dependencies. CoRR Manar Mazkatli, David Monschein, Johannes Grohmann, Anne Koziolek
2020	—	`conf`	Learning to Learn in Collective Adaptive Systems: Mining Design Patterns for Data-driven Reasoning. ACSOS Companion Mirko D'Angelo, Sona Ghahremani, Simos Gerasimou, Johannes Grohmann, Ingrid Nunes, Sven Tomforde, Evangelos Pournaras
2020	J	`jnl`	Learning to Learn in Collective Adaptive Systems: Mining Design Patterns for Data-driven Reasoning. CoRR Mirko D'Angelo, Sona Ghahremani, Simos Gerasimou, Johannes Grohmann, Ingrid Nunes, Sven Tomforde, Evangelos Pournaras
2020	—	`conf`	Model-Based Performance Predictions for SDN-Based Networks: A Case Study. MMB Stefan Herrnleben, Piotr Rygielski, Johannes Grohmann, Simon Eismann, Tobias Hoßfeld, Samuel Kounev
2020	—	`conf`	Optimizing Parametric Dependencies for Incremental Performance Model Extraction. ECSA Companion Sonya Voneva, Manar Mazkatli, Johannes Grohmann, Anne Koziolek
2020	B	`conf`	Predicting the Costs of Serverless Workflows. ICPE Simon Eismann, Johannes Grohmann, Erwin Van Eyk, Nikolas Herbst, Samuel Kounev
2020	J	`jnl`	Serverless Applications: Why, When, and How? CoRR Simon Eismann, Joel Scheuner, Erwin Van Eyk, Maximilian Schwinger, Johannes Grohmann, Cristina L. Abad, Alexandru Iosup
2020	J	`jnl`	Sizeless: Predicting the optimal size of serverless functions. CoRR Simon Eismann, Long Bui, Johannes Grohmann, Cristina L. Abad, Nikolas Herbst, Samuel Kounev
2020	—	`conf`	To Fail or Not to Fail: Predicting Hard Disk Drive Failure Time Windows. MMB Marwin Züfle, Christian Krupitzer, Florian Erhard, Johannes Grohmann, Samuel Kounev
2019	B	`conf`	Detecting Parametric Dependencies for Performance Models Using Feature Selection Techniques. MASCOTS Johannes Grohmann, Simon Eismann, Sven Elflein, Jóakim von Kistowski, Samuel Kounev, Manar Mazkatli
2019	B	`conf`	How is Performance Addressed in DevOps? ICPE Cor-Paul Bezemer, Simon Eismann, Vincenzo Ferme, Johannes Grohmann, Robert Heinrich, Pooyan Jamshidi, Weiyi Shang, André van Hoorn, Mónica Villavicencio, Jürgen Walter, Felix Willnecker
2019	A	`conf`	Integrating Statistical Response Time Models in Architectural Performance Models. ICSA Simon Eismann, Johannes Grohmann, Jürgen Walter, Jóakim von Kistowski, Samuel Kounev
2019	A	`conf`	Monitorless: Predicting Performance Degradation in Cloud Applications with Machine Learning. Middleware Johannes Grohmann, Patrick K. Nicholson, Jesus Omaña Iglesias, Samuel Kounev, Diego Lugones
2019	J	`jnl`	On Learning Parametric Dependencies from Monitoring Data. Softwaretechnik-Trends Johannes Grohmann, Simon Eismann, Samuel Kounev
2019	—	`conf`	On learning in collective self-adaptive systems: state of practice and a 3D framework. SEAMS@ICSE Mirko D'Angelo, Simos Gerasimou, Sona Ghahremani, Johannes Grohmann, Ingrid Nunes, Evangelos Pournaras, Sven Tomforde
2019	J	`jnl`	Online model learning for self-aware computing infrastructures. J. Syst. Softw. Simon Spinner, Johannes Grohmann, Simon Eismann, Samuel Kounev
2019	B	`conf`	Predicting Server Power Consumption from Standard Rating Results. ICPE Jóakim von Kistowski, Johannes Grohmann, Norbert Schmitt, Samuel Kounev
2019	—	`conf`	Systematic Search for Optimal Resource Configurations of Distributed Applications. FAS*W@SASO/ICAC André Bauer, Simon Eismann, Johannes Grohmann, Nikolas Herbst, Samuel Kounev
2019	—	`conf`	TeaStore - A Micro-Service Reference Application for Performance Engineers. ICPE Companion Jóakim von Kistowski, Simon Eismann, Johannes Grohmann, Norbert Schmitt, André Bauer, Samuel Kounev
2019	—	`conf`	TeaStore - A Micro-Service Reference Application. FAS*W@SASO/ICAC Simon Eismann, Jóakim von Kistowski, Johannes Grohmann, André Bauer, Norbert Schmitt, Samuel Kounev
2019	—	`conf`	TeaStore: A Micro-Service Reference Application for Benchmarking, Modeling and Resource Management Research. SE/SWM Jóakim von Kistowski, Simon Eismann, Norbert Schmitt, André Bauer, Johannes Grohmann, Samuel Kounev
2019	J	`jnl`	The SPEC-RG Reference Architecture for FaaS: From Microservices and Containers to Serverless Platforms. IEEE Internet Comput. Erwin Van Eyk, Alexandru Iosup, Johannes Grohmann, Simon Eismann, André Bauer, Laurens Versluis, Lucian Toader, Norbert Schmitt, Nikolas Herbst, Cristina L. Abad
2019	—	`conf`	Utilizing Clustering to Optimize Resource Demand Estimation Approaches. FAS*W@SASO/ICAC Johannes Grohmann, Simon Eismann, André Bauer, Marwin Züfle, Nikolas Herbst, Samuel Kounev
2018	—	`conf`	A SPEC RG Cloud Group's Vision on the Performance Challenges of FaaS Cloud Architectures. ICPE Companion Erwin Van Eyk, Alexandru Iosup, Cristina L. Abad, Johannes Grohmann, Simon Eismann
2018	—	`conf`	Blackbox Learning of Parametric Dependencies for Performance Models. MoDELS (Workshops) Vanessa Ackermann, Johannes Grohmann, Simon Eismann, Samuel Kounev
2018	J	`jnl`	How is Performance Addressed in DevOps? A Survey on Industrial Practices. CoRR Cor-Paul Bezemer, Simon Eismann, Vincenzo Ferme, Johannes Grohmann, Robert Heinrich, Pooyan Jamshidi, Weiyi Shang, André van Hoorn, Mónica Villavicencio, Jürgen Walter, Felix Willnecker
2018	—	`conf`	On the Value of Service Demand Estimation for Auto-scaling. MMB André Bauer, Johannes Grohmann, Nikolas Herbst, Samuel Kounev
2018	B	`conf`	TeaStore: A Micro-Service Reference Application for Benchmarking, Modeling and Resource Management Research. MASCOTS Jóakim von Kistowski, Simon Eismann, Norbert Schmitt, André Bauer, Johannes Grohmann, Samuel Kounev
2018	—	`conf`	TeaStore: A Micro-Service Reference Application for Cloud Researchers. UCC Companion Simon Eismann, Jóakim von Kistowski, Johannes Grohmann, André Bauer, Norbert Schmitt, Nikolas Herbst, Samuel Kounev
2018	—	`conf`	The Vision of Self-Aware Performance Models. ICSA Companion Johannes Grohmann, Simon Eismann, Samuel Kounev
2018	—	`conf`	Tools for Declarative Performance Engineering. ICPE Companion Jürgen Walter, Simon Eismann, Johannes Grohmann, Dusan Okanovic, Samuel Kounev
2018	C	`conf`	Using Machine Learning for Recommending Service Demand Estimation Approaches - Position Paper. CLOSER Johannes Grohmann, Nikolas Herbst, Simon Spinner, Samuel Kounev
2017	—	`conf`	Self-Tuning Resource Demand Estimation. ICAC Johannes Grohmann, Nikolas Herbst, Simon Spinner, Samuel Kounev