TELESTO: A Graph Neural Network Model for Anomaly Classification in Cloud Services. - Dominik Scheinert; Alexander Acker (ICSOC Workshops, 2020)

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 (IEEE BigData, 2021)

Training Data Reduction for Performance Models of Data Analytics Jobs in the Cloud. - Jonathan Will; Onur Arslan; Jonathan Bader; Dominik Scheinert; Lauritz Thamsen (IEEE BigData, 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 (CLUSTER, 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 (Euro-Par Workshops, 2021)

Evaluation of Load Prediction Techniques for Distributed Stream Processing. - Kain Kordian Gontarska; Morgan Geldenhuys; Dominik Scheinert; Philipp Wiesner; Andreas Polze; Lauritz Thamsen (IC2E, 2021)

C3O: Collaborative Cluster Configuration Optimization for Distributed Data Processing in Public Clouds. - Jonathan Will; Lauritz Thamsen; Dominik Scheinert; Jonathan Bader; Odej Kao (IC2E, 2021)

LogLAB: Attention-Based Labeling of Log Data Anomalies via Weak Supervision. - Thorsten Wittkopp; Philipp Wiesner; Dominik Scheinert; Alexander Acker (ICSOC, 2021)

A Taxonomy of Anomalies in Log Data. - Thorsten Wittkopp; Philipp Wiesner; Dominik Scheinert; Odej Kao (ICSOC Workshops, 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 (IPCCC, 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 (Middleware, 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)

Probabilistic Time Series Forecasting for Adaptive Monitoring in Edge Computing Environments. - Dominik Scheinert; Babak Sistani Zadeh Aghdam; Soeren Becker 001; Odej Kao; Lauritz Thamsen (IEEE Big Data, 2022)

Perona: Robust Infrastructure Fingerprinting for Resource-Efficient Big Data Analytics. - Dominik Scheinert; Soeren Becker 001; Jonathan Bader; Lauritz Thamsen; Jonathan Will; Odej Kao (IEEE Big Data, 2022)

Ruya: Memory-Aware Iterative Optimization of Cluster Configurations for Big Data Processing. - Jonathan Will; Lauritz Thamsen; Jonathan Bader; Dominik Scheinert; Odej Kao (IEEE Big Data, 2022)

Cucumber: Renewable-Aware Admission Control for Delay-Tolerant Cloud and Edge Workloads. - Philipp Wiesner; Dominik Scheinert; Thorsten Wittkopp; Lauritz Thamsen; Odej Kao (Euro-Par, 2022)

Khaos: Dynamically Optimizing Checkpointing for Dependable Distributed Stream Processing. - Morgan Geldenhuys; Benjamin J. J. Pfister; Dominik Scheinert; Lauritz Thamsen; Odej Kao (FedCSIS, 2022)

A2Log: Attentive Augmented Log Anomaly Detection. - Thorsten Wittkopp; Alexander Acker; Sasho Nedelkoski; Jasmin Bogatinovski; Dominik Scheinert; Wu Fan; Odej Kao (HICSS, 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 (IC2E, 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 (IC2E, 2022)

Efficient Runtime Profiling for Black-box Machine Learning Services on Sensor Streams. - Soeren Becker 001; Dominik Scheinert; Florian Schmidt 006; Odej Kao (ICFEC, 2022)

Phoebe: QoS-Aware Distributed Stream Processing through Anticipating Dynamic Workloads. - Morgan K. Geldenhuys; Dominik Scheinert; Odej Kao; Lauritz Thamsen (ICWS, 2022)

Scalable and Data-driven Decision Support in the Maintenance, Repair, and Overhaul Process. - Houkun Zhu; Helena Ebel; Dominik Scheinert; Florian Schmidt 006; Jens Altenkirch; Odej Kao (IEEM, 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 (IPCCC, 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)

Towards a Peer-to-Peer Data Distribution Layer for Efficient and Collaborative Resource Optimization of Distributed Dataflow Applications. - Dominik Scheinert; Sören Becker 001; Jonathan Will; Luis Englaender; Lauritz Thamsen (IEEE Big Data, 2023)

PULL: Reactive Log Anomaly Detection Based On Iterative PU Learning. - Thorsten Wittkopp; Dominik Scheinert; Philipp Wiesner; Alexander Acker; Odej Kao (HICSS, 2023)

Evaluation of Data Enrichment Methods for Distributed Stream Processing Systems. - Dominik Scheinert; Fabian Casares; Morgan K. Geldenhuys; Kevin Styp-Rekowski; Odej Kao (IC2E, 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 (IPCCC, 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 (SSDBM, 2023)

Challenges and Future Directions in Similarity Assessment of Big Data Analytics Workloads. - Dominik Scheinert; Alexander Guttenberger; Jonathan Will; Odej Kao (IEEE Big Data, 2024)

Sizey: Memory-Efficient Execution of Scientific Workflow Tasks. - Jonathan Bader; Fabian Skalski; Fabian Lehmann; Dominik Scheinert; Jonathan Will; Lauritz Thamsen; Odej Kao (CLUSTER, 2024)

Demeter: Resource-Efficient Distributed Stream Processing under Dynamic Loads with Multi-Configuration Optimization. - Morgan K. Geldenhuys; Dominik Scheinert; Odej Kao; Lauritz Thamsen (ICPE, 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 (ICPE, 2024)

Privacy-Preserving Sharing of Data Analytics Runtime Metrics for Performance Modeling. - Jonathan Will; Dominik Scheinert; Seraphin Zunzer; Jan Bode; Cedric Kring; Lauritz Thamsen (ICPE (Companion), 2024)

Methods for the adaptive provisioning of resources to iterative batch jobs. - Dominik Scheinert (2024)