Dominik Scheinert

Orcid: 0000-0003-0763-3233

According to our database1, Dominik Scheinert authored at least 33 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Privacy-Preserving Sharing of Data Analytics Runtime Metrics for Performance Modeling.
CoRR, 2024

Demeter: Resource-Efficient Distributed Stream Processing under Dynamic Loads with Multi-Configuration Optimization.
CoRR, 2024

Daedalus: Self-Adaptive Horizontal Autoscaling for Resource Efficiency of Distributed Stream Processing Systems.
CoRR, 2024

2023
Karasu: A Collaborative Approach to Efficient Cluster Configuration for Big Data Analytics.
CoRR, 2023

Selecting Efficient Cluster Resources for Data Analytics: When and How to Allocate for In-Memory Processing?
Proceedings of the 35th International Conference on Scientific and Statistical Database Management, 2023

Evaluation of Data Enrichment Methods for Distributed Stream Processing Systems.
Proceedings of the IEEE International Conference on Cloud Engineering, 2023

PULL: Reactive Log Anomaly Detection Based On Iterative PU Learning.
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.
Proceedings of the IEEE International Conference on Big Data, 2023

2022
Collaborative Cluster Configuration for Distributed Data-Parallel Processing: A Research Overview.
Datenbank-Spektrum, 2022

Reshi: Recommending Resources for Scientific Workflow Tasks on Heterogeneous Infrastructures.
Proceedings of the IEEE International Performance, 2022

Scalable and Data-driven Decision Support in the Maintenance, Repair, and Overhaul Process.
Proceedings of the IEEE International Conference on Industrial Engineering and Engineering Management, 2022

Phoebe: QoS-Aware Distributed Stream Processing through Anticipating Dynamic Workloads.
Proceedings of the IEEE International Conference on Web Services, 2022

Efficient Runtime Profiling for Black-box Machine Learning Services on Sensor Streams.
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.
Proceedings of the IEEE International Conference on Cloud Engineering, 2022

Get Your Memory Right: The Crispy Resource Allocation Assistant for Large-Scale Data Processing.
Proceedings of the IEEE International Conference on Cloud Engineering, 2022

A2Log: Attentive Augmented Log Anomaly Detection.
Proceedings of the 55th Hawaii International Conference on System Sciences, 2022

Khaos: Dynamically Optimizing Checkpointing for Dependable Distributed Stream Processing.
Proceedings of the 17th Conference on Computer Science and Intelligence Systems, 2022

Cucumber: Renewable-Aware Admission Control for Delay-Tolerant Cloud and Edge Workloads.
Proceedings of the Euro-Par 2022: Parallel Processing, 2022

Ruya: Memory-Aware Iterative Optimization of Cluster Configurations for Big Data Processing.
Proceedings of the IEEE International Conference on Big Data, 2022

Perona: Robust Infrastructure Fingerprinting for Resource-Efficient Big Data Analytics.
Proceedings of the IEEE International Conference on Big Data, 2022

Probabilistic Time Series Forecasting for Adaptive Monitoring in Edge Computing Environments.
Proceedings of the IEEE International Conference on Big Data, 2022

2021
Learning Dependencies in Distributed Cloud Applications to Identify and Localize Anomalies.
CoRR, 2021

Let's wait awhile: how temporal workload shifting can reduce carbon emissions in the cloud.
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.
Proceedings of the IEEE International Performance, 2021

A Taxonomy of Anomalies in Log Data.
Proceedings of the Service-Oriented Computing - ICSOC 2021 Workshops, 2021

LogLAB: Attention-Based Labeling of Log Data Anomalies via Weak Supervision.
Proceedings of the Service-Oriented Computing - 19th International Conference, 2021

C3O: Collaborative Cluster Configuration Optimization for Distributed Data Processing in Public Clouds.
Proceedings of the IEEE International Conference on Cloud Engineering, 2021

Evaluation of Load Prediction Techniques for Distributed Stream Processing.
Proceedings of the IEEE International Conference on Cloud Engineering, 2021

Rafiki: Task-Level Capacity Planning in Distributed Stream Processing Systems.
Proceedings of the Euro-Par 2021: Parallel Processing Workshops, 2021

Bellamy: Reusing Performance Models for Distributed Dataflow Jobs Across Contexts.
Proceedings of the IEEE International Conference on Cluster Computing, 2021

Training Data Reduction for Performance Models of Data Analytics Jobs in the Cloud.
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.
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.
Proceedings of the Service-Oriented Computing - ICSOC 2020 Workshops, 2020


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