Dominik Scheinert

According to our database, Dominik Scheinert authored at least 34 papers between 2020 and 2024.

Collaborative distances:

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

2024

Sizey: Memory-Efficient Execution of Scientific Workflow Tasks.

Jonathan Bader, Fabian Skalski, Fabian Lehmann, Dominik Scheinert, Jonathan Will, Lauritz Thamsen, Odej Kao

CoRR, 2024

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

Jonathan Will, Dominik Scheinert, Seraphin Zunzer, Jan Bode, Cedric Kring, Lauritz Thamsen

Proceedings of the Companion of the 15th ACM/SPEC International Conference on Performance Engineering, 2024

Daedalus: Self-Adaptive Horizontal Autoscaling for Resource Efficiency of Distributed Stream Processing Systems.

Benjamin J. J. Pfister, Dominik Scheinert, Morgan K. Geldenhuys, Odej Kao

Proceedings of the 15th ACM/SPEC International Conference on Performance Engineering, 2024

Demeter: Resource-Efficient Distributed Stream Processing under Dynamic Loads with Multi-Configuration Optimization.

Morgan K. Geldenhuys, Dominik Scheinert, Odej Kao, Lauritz Thamsen

Proceedings of the 15th ACM/SPEC International Conference on Performance Engineering, 2024

2023

Karasu: A Collaborative Approach to Efficient Cluster Configuration for Big Data Analytics.

Dominik Scheinert, Philipp Wiesner, Thorsten Wittkopp, Lauritz Thamsen, Jonathan Will, Odej Kao

CoRR, 2023

Selecting Efficient Cluster Resources for Data Analytics: When and How to Allocate for In-Memory Processing?

Jonathan Will, Lauritz Thamsen, Dominik Scheinert, Odej Kao

Proceedings of the 35th International Conference on Scientific and Statistical Database Management, 2023

Evaluation of Data Enrichment Methods for Distributed Stream Processing Systems.

Dominik Scheinert, Fabian Casares, Morgan K. Geldenhuys, Kevin Styp-Rekowski, Odej Kao

Proceedings of the IEEE International Conference on Cloud Engineering, 2023

PULL: Reactive Log Anomaly Detection Based On Iterative PU Learning.

Thorsten Wittkopp, Dominik Scheinert, Philipp Wiesner, Alexander Acker, Odej Kao

Proceedings of the 56th Hawaii International Conference on System Sciences, 2023

Towards a Peer-to-Peer Data Distribution Layer for Efficient and Collaborative Resource Optimization of Distributed Dataflow Applications.

Dominik Scheinert, Sören Becker, Jonathan Will, Luis Englaender, Lauritz Thamsen

Proceedings of the IEEE International Conference on Big Data, 2023

2022

Collaborative Cluster Configuration for Distributed Data-Parallel Processing: A Research Overview.

Lauritz Thamsen, Dominik Scheinert, Jonathan Will, Jonathan Bader, Odej Kao

Datenbank-Spektrum, 2022

Reshi: Recommending Resources for Scientific Workflow Tasks on Heterogeneous Infrastructures.

Jonathan Bader, Fabian Lehmann, Alexander Groth, Lauritz Thamsen, Dominik Scheinert, Jonathan Will, Ulf Leser, Odej Kao

Proceedings of the IEEE International Performance, 2022

Scalable and Data-driven Decision Support in the Maintenance, Repair, and Overhaul Process.

Houkun Zhu, Helena Ebel, Dominik Scheinert, Florian Schmidt, Jens Altenkirch, Odej Kao

Proceedings of the IEEE International Conference on Industrial Engineering and Engineering Management, 2022

Phoebe: QoS-Aware Distributed Stream Processing through Anticipating Dynamic Workloads.

Morgan K. Geldenhuys, Dominik Scheinert, Odej Kao, Lauritz Thamsen

Proceedings of the IEEE International Conference on Web Services, 2022

Efficient Runtime Profiling for Black-box Machine Learning Services on Sensor Streams.

Soeren Becker, Dominik Scheinert, Florian Schmidt, Odej Kao

Proceedings of the 6th IEEE International Conference on Fog and Edge Computing, 2022

Magpie: Automatically Tuning Static Parameters for Distributed File Systems using Deep Reinforcement Learning.

Houkun Zhu, Dominik Scheinert, Lauritz Thamsen, Kain Kordian Gontarska, Odej Kao

Proceedings of the IEEE International Conference on Cloud Engineering, 2022

Get Your Memory Right: The Crispy Resource Allocation Assistant for Large-Scale Data Processing.

Jonathan Will, Lauritz Thamsen, Jonathan Bader, Dominik Scheinert, Odej Kao

Proceedings of the IEEE International Conference on Cloud Engineering, 2022

A2Log: Attentive Augmented Log Anomaly Detection.

Thorsten Wittkopp, Alexander Acker, Sasho Nedelkoski, Jasmin Bogatinovski, Dominik Scheinert, Wu Fan, Odej Kao

Proceedings of the 55th Hawaii International Conference on System Sciences, 2022

Khaos: Dynamically Optimizing Checkpointing for Dependable Distributed Stream Processing.

Morgan Geldenhuys, Benjamin J. J. Pfister, Dominik Scheinert, Lauritz Thamsen, Odej Kao

Proceedings of the 17th Conference on Computer Science and Intelligence Systems, 2022

Cucumber: Renewable-Aware Admission Control for Delay-Tolerant Cloud and Edge Workloads.

Philipp Wiesner, Dominik Scheinert, Thorsten Wittkopp, Lauritz Thamsen, Odej Kao

Proceedings of the Euro-Par 2022: Parallel Processing, 2022

Ruya: Memory-Aware Iterative Optimization of Cluster Configurations for Big Data Processing.

Jonathan Will, Lauritz Thamsen, Jonathan Bader, Dominik Scheinert, Odej Kao

Proceedings of the IEEE International Conference on Big Data, 2022

Perona: Robust Infrastructure Fingerprinting for Resource-Efficient Big Data Analytics.

Dominik Scheinert, Soeren Becker, Jonathan Bader, Lauritz Thamsen, Jonathan Will, Odej Kao

Proceedings of the IEEE International Conference on Big Data, 2022

Probabilistic Time Series Forecasting for Adaptive Monitoring in Edge Computing Environments.

Dominik Scheinert, Babak Sistani Zadeh Aghdam, Soeren Becker, Odej Kao, Lauritz Thamsen

Proceedings of the IEEE International Conference on Big Data, 2022

2021

Learning Dependencies in Distributed Cloud Applications to Identify and Localize Anomalies.

Dominik Scheinert, Alexander Acker, Lauritz Thamsen, Morgan K. Geldenhuys, Odej Kao

CoRR, 2021

Let's wait awhile: how temporal workload shifting can reduce carbon emissions in the cloud.

Philipp Wiesner, Ilja Behnke, Dominik Scheinert, Kain Kordian Gontarska, Lauritz Thamsen

Proceedings of the Middleware '21: 22nd International Middleware Conference, Québec City, Canada, December 6, 2021

Enel: Context-Aware Dynamic Scaling of Distributed Dataflow Jobs using Graph Propagation.

Dominik Scheinert, Houkun Zhu, Lauritz Thamsen, Morgan K. Geldenhuys, Jonathan Will, Alexander Acker, Odej Kao

Proceedings of the IEEE International Performance, 2021

A Taxonomy of Anomalies in Log Data.

Thorsten Wittkopp, Philipp Wiesner, Dominik Scheinert, Odej Kao

Proceedings of the Service-Oriented Computing - ICSOC 2021 Workshops, 2021

LogLAB: Attention-Based Labeling of Log Data Anomalies via Weak Supervision.

Thorsten Wittkopp, Philipp Wiesner, Dominik Scheinert, Alexander Acker

Proceedings of the Service-Oriented Computing - 19th International Conference, 2021

C3O: Collaborative Cluster Configuration Optimization for Distributed Data Processing in Public Clouds.

Jonathan Will, Lauritz Thamsen, Dominik Scheinert, Jonathan Bader, Odej Kao

Proceedings of the IEEE International Conference on Cloud Engineering, 2021

Evaluation of Load Prediction Techniques for Distributed Stream Processing.

Kain Kordian Gontarska, Morgan Geldenhuys, Dominik Scheinert, Philipp Wiesner, Andreas Polze, Lauritz Thamsen

Proceedings of the IEEE International Conference on Cloud Engineering, 2021

Rafiki: Task-Level Capacity Planning in Distributed Stream Processing Systems.

Benjamin J. J. Pfister, Wolf S. Lickefett, Jan Nitschke, Sumit Paul, Morgan K. Geldenhuys, Dominik Scheinert, Kain Kordian Gontarska, Lauritz Thamsen

Proceedings of the Euro-Par 2021: Parallel Processing Workshops, 2021

Bellamy: Reusing Performance Models for Distributed Dataflow Jobs Across Contexts.

Dominik Scheinert, Lauritz Thamsen, Houkun Zhu, Jonathan Will, Alexander Acker, Thorsten Wittkopp, Odej Kao

Proceedings of the IEEE International Conference on Cluster Computing, 2021

Training Data Reduction for Performance Models of Data Analytics Jobs in the Cloud.

Jonathan Will, Onur Arslan, Jonathan Bader, Dominik Scheinert, Lauritz Thamsen

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

On the Potential of Execution Traces for Batch Processing Workload Optimization in Public Clouds.

Dominik Scheinert, Alireza Alamgiralem, Jonathan Bader, Jonathan Will, Thorsten Wittkopp, Lauritz Thamsen

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020

TELESTO: A Graph Neural Network Model for Anomaly Classification in Cloud Services.

Dominik Scheinert, Alexander Acker

Proceedings of the Service-Oriented Computing - ICSOC 2020 Workshops, 2020