Sören Henning

Orcid: 0000-0001-6912-2549

According to our database1, Sören Henning authored at least 49 papers between 2017 and 2024.

Collaborative distances:

Timeline

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
15th Symposium on Software Performance 2024.
Softwaretechnik-Trends, November, 2024

Scalability Benchmarking of Cloud-Native Applications: The Theodolite Approach.
Softwaretechnik-Trends, May, 2024

Replication Package for: ShuffleBench: A Benchmark for Large-Scale Data Shuffling Operations with Distributed Stream Processing Frameworks.
Dataset, March, 2024

Benchmarking scalability of stream processing frameworks deployed as microservices in the cloud.
J. Syst. Softw., February, 2024

Replication Package for: ShuffleBench: A Benchmark for Large-Scale Data Shuffling Operations with Distributed Stream Processing Frameworks.
Dataset, February, 2024

Replication Package for: ShuffleBench: A Benchmark for Large-Scale Data Shuffling Operations with Distributed Stream Processing Frameworks.
Dataset, February, 2024

Analyzing Logs of Large-Scale Software Systems using Time Curves Visualization.
CoRR, 2024

High-level Stream Processing: A Complementary Analysis of Fault Recovery.
CoRR, 2024

ShuffleBench: A Benchmark for Large-Scale Data Shuffling Operations with Distributed Stream Processing Frameworks.
Proceedings of the 15th ACM/SPEC International Conference on Performance Engineering, 2024

A Comprehensive Benchmarking Analysis of Fault Recovery in Stream Processing Frameworks.
Proceedings of the 18th ACM International Conference on Distributed and Event-based Systems, 2024

2023
Benchmarking Function Hook Latency in Cloud-Native Environments.
Softwaretechnik-Trends, November, 2023

Benchmarking Stream Processing Frameworks for Large Scale Data Shuffling.
Softwaretechnik-Trends, November, 2023

Theodolite.
Dataset, July, 2023

Replication Package for: Benchmarking scalability of stream processing frameworks deployed as microservices in the cloud.
Dataset, June, 2023

Replication Package for: Benchmarking scalability of stream processing frameworks deployed as microservices in the cloud.
Dataset, June, 2023

Theodolite.
Dataset, April, 2023

Cloud-Native Scalability Benchmarking with Theodolite: Applied to the TeaStore Benchmark.
Softwaretechnik-Trends, February, 2023

Theodolite.
Dataset, February, 2023

Theodolite.
Dataset, February, 2023

Theodolite.
Dataset, January, 2023

Scalability Benchmarking of Cloud-Native Applications Applied to Event-Driven Microservices.
PhD thesis, 2023

Benchmarking scalability of stream processing frameworks deployed as event-driven microservices in the cloud.
CoRR, 2023

Benchmarking Scalability of Cloud-Native Applications.
Proceedings of the Software Engineering 2023, 2023

A systematic mapping of performance in distributed stream processing systems.
Proceedings of the 49th Euromicro Conference on Software Engineering and Advanced Applications, 2023

2022
Replication Package for: Benchmarking scalability of stream processing frameworks deployed as microservices in the cloud.
Dataset, December, 2022

Theodolite.
Dataset, November, 2022

Replication Package for: Streaming vs. Functions: A Cost Perspective on Cloud Event Processing.
Dataset, April, 2022

A configurable method for benchmarking scalability of cloud-native applications.
Empir. Softw. Eng., 2022

Streaming vs. Functions: A Cost Perspective on Cloud Event Processing.
Proceedings of the IEEE International Conference on Cloud Engineering, 2022

Demo Paper: Benchmarking Scalability of Cloud-Native Applications with Theodolite.
Proceedings of the IEEE International Conference on Cloud Engineering, 2022

2021
Replication Package for: A Configurable Method for Benchmarking Scalability of Cloud-Native Applications.
Dataset, October, 2021

Replication Package for: Theodolite: Scalability Benchmarking of Distributed Stream Processing Engines in Microservice Architectures.
Dataset, January, 2021

The Titan Control Center for Industrial DevOps analytics research.
Softw. Impacts, 2021

Theodolite: Scalability Benchmarking of Distributed Stream Processing Engines in Microservice Architectures.
Big Data Res., 2021

How to Measure Scalability of Distributed Stream Processing Engines?
Proceedings of the ICPE '21: ACM/SPEC International Conference on Performance Engineering, 2021

Reproducible Benchmarking of Cloud-Native Applications With the Kubernetes Operator Pattern.
Proceedings of the Short Paper Proceedings of Symposium on Software Performance 2021, 2021

2020
Replication Package for: Scalable and Reliable Multi-Dimensional Sensor Data Aggregation in Data-Streaming Architectures.
Dataset, April, 2020

Toward Efficient Scalability Benchmarking of Event-Driven Microservice Architectures at Large Scale.
Softwaretechnik-Trends, 2020

Complexity and Inapproximability Results for Parallel Task Scheduling and Strip Packing.
Theory Comput. Syst., 2020

Goals and Measures for Analyzing Power Consumption Data in Manufacturing Enterprises.
CoRR, 2020

Theodolite: Scalability Benchmarking of Distributed Stream Processing Engines.
CoRR, 2020

2019
Replication Package for: Scalable and Reliable Multi-Dimensional Aggregation of Sensor Data Streams.
Dataset, December, 2019

Replication Package for: Scalable and Reliable Multi-Dimensional Aggregation of Sensor Data Streams.
Dataset, December, 2019

Monitoring Electrical Power Consumption with Kieker.
Softwaretechnik-Trends, 2019

Clean Code: On the Use of Practices and Tools to Produce Maintainable Code for Long-Living Software.
Proceedings of the Workshops of the Software Engineering Conference 2019, 2019

Industrial DevOps.
Proceedings of the IEEE International Conference on Software Architecture Companion, 2019

A Scalable Architecture for Power Consumption Monitoring in Industrial Production Environments.
Proceedings of the IEEE International Conference on Fog Computing, 2019

Scalable and Reliable Multi-Dimensional Aggregation of Sensor Data Streams.
Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2017
RadarGun: Toward a Performance Testing Framework.
Softwaretechnik-Trends, 2017


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