Johannes Rank

According to our database, Johannes Rank authored at least 11 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Evaluating Task-Level CPU Efficiency for Distributed Stream Processing Systems.

Johannes Rank, Jonas Herget, Andreas Hein, Helmut Krcmar

Big Data Cogn. Comput., March, 2023

The Role of Performance in Streaming Analytics Projects: Expert Interviews on Current Challenges and Future Research Directions.

Johannes Rank, Andreas Hein, Helmut Krcmar

Softwaretechnik-Trends, February, 2023

Predicting Scaling Efficiency of Distributed Stream Processing Systems via Task Level Performance Simulation.

Johannes Rank, Maximilian Barnert, Andreas Hein, Helmut Krcmar

Softwaretechnik-Trends, February, 2023

2022

Task Level Performance - Datasets and Analysis.

Johannes Rank

Dataset, December, 2022

ProteomicsDB: toward a FAIR open-source resource for life-science research.

Ludwig Lautenbacher, Patroklos Samaras, Julian Müller, Andreas Grafberger, Marwin Shraideh, Johannes Rank, Simon T. Fuchs, Tobias K. Schmidt, Matthew The, Christian Dallago, Holger Wittges, Burkhard Rost, Helmut Krcmar, Bernhard Küster, Mathias Wilhelm

Nucleic Acids Res., 2022

2020

A Dynamic Resource Demand Analysis Approach for Stream Processing Systems.

Johannes Rank, Andreas Hein, Helmut Krcmar

Softwaretechnik-Trends, 2020

ProteomicsDB: a multi-omics and multi-organism resource for life science research.

Patroklos Samaras, Tobias Schmidt, Martin Frejno, Siegfried Gessulat, Maria Reinecke, Anna Jarzab, Jana Zecha, Julia Mergner, Piero Giansanti, Hans-Christian Ehrlich, Stephan Aiche, Johannes Rank, Harald Kienegger, Helmut Krcmar, Bernhard Küster, Mathias Wilhelm

Nucleic Acids Res., 2020

2019

Towards Model-based Performance Predictions of SAP Enterprise.

Adrian Streitz, Maximilian Barnert, Johannes Rank, Harald Kienegger, Helmut Krcmar

Softwaretechnik-Trends, 2019

Using OPEN.xtrace and Architecture-Level Models to Predict Workload Performance on In-Memory Database Systems.

Maximilian Barnert, Adrian Streitz, Johannes Rank, Harald Kienegger, Helmut Krcmar

Softwaretechnik-Trends, 2019

Towards Performance Prediction for Stream Processing Applications.

Johannes Rank, Dominik Paluch, Harald Kienegger, Helmut Krcmar

Proceedings of the 31st GI-Workshop Grundlagen von Datenbanken, Saarburg, 2019

Monitoring Thread-Related Resource Demands of a Multi-Tenant In-Memory Database in a Cloud Environment.

Dominik Paluch, Johannes Rank, Harald Kienegger, Helmut Krcmar

Proceedings of the 31st GI-Workshop Grundlagen von Datenbanken, Saarburg, 2019