Design and Evaluation of a Proactive, Application-Aware Auto-Scaler: Tutorial Paper. - André Bauer 001; Nikolas Herbst; Samuel Kounev (ICPE, 2017)

On the Value of Service Demand Estimation for Auto-scaling. - André Bauer 001; Johannes Grohmann; Nikolas Herbst; Samuel Kounev (MMB, 2018)

TeaStore: A Micro-Service Reference Application for Cloud Researchers. - Simon Eismann; Jóakim von Kistowski; Johannes Grohmann; André Bauer 001; Norbert Schmitt; Nikolas Herbst; Samuel Kounev (UCC Companion, 2018)

FOX: Cost-Awareness for Autonomic Resource Management in Public Clouds. - Veronika Lesch; André Bauer 001; Nikolas Herbst; Samuel Kounev (ICPE, 2018)

Quantifying Cloud Performance and Dependability: Taxonomy, Metric Design, and Emerging Challenges. - Nikolas Herbst; André Bauer 001; Samuel Kounev; Giorgos Oikonomou; Erwin Van Eyk; George Kousiouris; Athanasia Evangelinou; Rouven Krebs; Tim Brecht; Cristina L. Abad; Alexandru Iosup (ACM Trans. Model. Perform. Evaluation Comput. Syst., 2018)

An Experimental Performance Evaluation of Autoscalers for Complex Workflows. - Alexey Ilyushkin; Ahmed Ali-Eldin; Nikolas Herbst; André Bauer 001; Alessandro Vittorio Papadopoulos; Dick H. J. Epema; Alexandru Iosup (ACM Trans. Model. Perform. Evaluation Comput. Syst., 2018)

Kaa: Evaluating Elasticity of Cloud-Hosted DBMS. - Daniel Seybold; Simon Volpert; Stefan Wesner; André Bauer 001; Nikolas Herbst; Jörg Domaschka (CloudCom, 2019)

Online Power Consumption Estimation for Functions in Cloud Applications. - Norbert Schmitt; Lukas Iffländer; André Bauer 001; Samuel Kounev (ICAC, 2019)

Autonomic Forecasting Method Selection: Examination and Ways Ahead. - Marwin Züfle; André Bauer 001; Veronika Lesch; Christian Krupitzer; Nikolas Herbst; Samuel Kounev; Valentin Curtef (ICAC, 2019)

Chamulteon: Coordinated Auto-Scaling of Micro-Services. - André Bauer 001; Veronika Lesch; Laurens Versluis; Alexey Ilyushkin; Nikolas Herbst; Samuel Kounev (ICDCS, 2019)

Systematic Search for Optimal Resource Configurations of Distributed Applications. - André Bauer 001; Simon Eismann; Johannes Grohmann; Nikolas Herbst; Samuel Kounev (FAS*W@SASO/ICAC, 2019)

Best Practices for Time Series Forecasting (Tutorial). - André Bauer 001; Marwin Züfle; Nikolas Herbst; Samuel Kounev (FAS*W@SASO/ICAC, 2019)

TeaStore - A Micro-Service Reference Application. - Simon Eismann; Jóakim von Kistowski; Johannes Grohmann; André Bauer 001; Norbert Schmitt; Samuel Kounev (FAS*W@SASO/ICAC, 2019)

Utilizing Clustering to Optimize Resource Demand Estimation Approaches. - Johannes Grohmann; Simon Eismann; André Bauer 001; Marwin Züfle; Nikolas Herbst; Samuel Kounev (FAS*W@SASO/ICAC, 2019)

TeaStore: A Micro-Service Reference Application for Benchmarking, Modeling and Resource Management Research. - Jóakim von Kistowski; Simon Eismann; Norbert Schmitt; André Bauer 001; Johannes Grohmann; Samuel Kounev (SE/SWM, 2019)

TeaStore - A Micro-Service Reference Application for Performance Engineers. - Jóakim von Kistowski; Simon Eismann; Johannes Grohmann; Norbert Schmitt; André Bauer 001; Samuel Kounev (ICPE Companion, 2019)

Performance-Feedback Autoscaling with Budget Constraints for Cloud-based Workloads of Workflows. - Alexey Ilyushkin; André Bauer 001; Alessandro Vittorio Papadopoulos; Ewa Deelman; Alexandru Iosup (CoRR, 2019)

The SPEC-RG Reference Architecture for FaaS: From Microservices and Containers to Serverless Platforms. - Erwin Van Eyk; Alexandru Iosup; Johannes Grohmann; Simon Eismann; André Bauer 001; Laurens Versluis; Lucian Toader; Norbert Schmitt; Nikolas Herbst; Cristina L. Abad (IEEE Internet Comput., 2019)

Modeling of Aggregated IoT Traffic and Its Application to an IoT Cloud. - Florian Metzger; Tobias Hoßfeld; André Bauer 001; Samuel Kounev; Poul E. Heegaard (Proc. IEEE, 2019)

Chameleon: A Hybrid, Proactive Auto-Scaling Mechanism on a Level-Playing Field. - André Bauer 001; Nikolas Herbst; Simon Spinner; Ahmed Ali-Eldin; Samuel Kounev (IEEE Trans. Parallel Distributed Syst., 2019)

Telescope: An Automatic Feature Extraction and Transformation Approach for Time Series Forecasting on a Level-Playing Field. - André Bauer 001; Marwin Züfle; Nikolas Herbst; Samuel Kounev; Valentin Curtef (ICDE, 2020)

An Automated Forecasting Framework based on Method Recommendation for Seasonal Time Series. - André Bauer 001; Marwin Züfle; Johannes Grohmann; Norbert Schmitt; Nikolas Herbst; Samuel Kounev (ICPE, 2020)

Time Series Forecasting for Self-Aware Systems. - André Bauer 001; Marwin Züfle; Nikolas Herbst; Albin Zehe; Andreas Hotho; Samuel Kounev (Proc. IEEE, 2020)

Automatisierte Hybride Zeitreihenprognose. - André Bauer 001 (Ausgezeichnete Informatikdissertationen, 2020)

Benchmarking of Pre- and Post-Quantum Group Encryption Schemes with Focus on IoT. - Thomas Prantl; Dominik Prantl; André Bauer 001; Lukas Iffländer; Alexandra Dmitrienko; Samuel Kounev; Christian Krupitzer (IPCCC, 2021)

Towards Splitting Monolithic Workflows Into Serverless Functions and Estimating Their Run-Time in the Earth Observation Domain (Poster). - Dennis Kaiser; Bohdan Dovhan; André Bauer 001; Samuel Kounev (SSP, 2021)

Libra: A Benchmark for Time Series Forecasting Methods. - André Bauer 001; Marwin Züfle; Simon Eismann; Johannes Grohmann; Nikolas Herbst; Samuel Kounev (ICPE, 2021)

SARDE: A Framework for Continuous and Self-Adaptive Resource Demand Estimation. - Johannes Grohmann; Simon Eismann; André Bauer 001; Simon Spinner; Johannes Blum 001; Nikolas Herbst; Samuel Kounev (ACM Trans. Auton. Adapt. Syst., 2021)

Methodological Principles for Reproducible Performance Evaluation in Cloud Computing. - Alessandro Vittorio Papadopoulos; Laurens Versluis; André Bauer 001; Nikolas Herbst; Jóakim von Kistowski; Ahmed Ali-Eldin; Cristina L. Abad; José Nelson Amaral; Petr Tuma 001; Alexandru Iosup (IEEE Trans. Software Eng., 2021)

Automated Hybrid Time Series Forecasting: Design, Benchmarking, and Use Cases. - André Bauer 001 (2021)

An Experience Report on the Suitability of a Distributed Group Encryption Scheme for an IoT Use Case. - Thomas Prantl; Simon Engel; André Bauer 001; Ala Eddine Ben Yahya; Stefan Herrnleben; Lukas Iffländer; Alexandra Dmitrienko; Samuel Kounev (VTC Spring, 2022)

SPEC Research - Introducing the Predictive Data Analytics Working Group: Poster Paper. - André Bauer 001; Mark Leznik; Md Shahriar Iqbal; Daniel Seybold; Igor Trubin; Benjamin Erb; Jörg Domaschka; Pooyan Jamshidi (ICPE (Companion), 2022)

Automated Triage of Performance Change Points Using Time Series Analysis and Machine Learning: Data Challenge Paper. - André Bauer 001; Martin Straesser; Lukas Beierlieb; Maximilian Meissner; Samuel Kounev (ICPE (Companion), 2022)

Same, Same, but Dissimilar: Exploring Measurements for Workload Time-series Similarity. - Mark Leznik; Johannes Grohmann; Nina Kliche; André Bauer 001; Daniel Seybold; Simon Eismann; Samuel Kounev; Jörg Domaschka (ICPE, 2022)

Change Point Detection for MongoDB Time Series Performance Regression. - Mark Leznik; Md Shahriar Iqbal; Igor Trubin; Arne Lochner; Pooyan Jamshidi; André Bauer 001 (ICPE (Companion), 2022)

Why Is It Not Solved Yet?: Challenges for Production-Ready Autoscaling. - Martin Straesser; Johannes Grohmann; Jóakim von Kistowski; Simon Eismann; André Bauer 001; Samuel Kounev (ICPE, 2022)

A Survey on Secure Group Communication Schemes With Focus on IoT Communication. - Thomas Prantl; Timo Zeck; André Bauer 001; Peter Ten; Dominik Prantl; Ala Eddine Ben Yahya; Lukas Iffländer; Alexandra Dmitrienko; Christian Krupitzer; Samuel Kounev (IEEE Access, 2022)

Towards Forecasting Future Snow Cover Dynamics in the European Alps - The Potential of Long Optical Remote-Sensing Time Series. - Jonas Köhler 002; André Bauer 001; Andreas J. Dietz; Claudia Kuenzer (Remote. Sens., 2022)

Trillion Parameter AI Serving Infrastructure for Scientific Discovery: A Survey and Vision. - Nathaniel Hudson; J. Gregory Pauloski; Matt Baughman; Alok Kamatar; Mansi Sakarvadia; Logan T. Ward; Ryan Chard; André Bauer 001; Maksim Levental; Wenyi Wang; Will Engler; Owen Price Skelly; et al. (BDCAT, 2023)

Memory Injections: Correcting Multi-Hop Reasoning Failures During Inference in Transformer-Based Language Models. - Mansi Sakarvadia; Aswathy Ajith; Arham Khan; Daniel Grzenda; Nathaniel Hudson; André Bauer 001; Kyle Chard; Ian T. Foster (BlackboxNLP@EMNLP, 2023)

An Empirical Study of Container Image Configurations and Their Impact on Start Times. - Martin Straesser; André Bauer 001; Robert Leppich; Nikolas Herbst; Kyle Chard; Ian T. Foster; Samuel Kounev (CCGrid, 2023)

Performance Impact Analysis of Homomorphic Encryption: A Case Study Using Linear Regression as an Example. - Thomas Prantl; Simon Engel; Lukas Horn; Dennis Kaiser; Lukas Iffländer; André Bauer 001; Christian Krupitzer; Samuel Kounev (ISPEC, 2023)

Tournament-Based Pretraining to Accelerate Federated Learning. - Matt Baughman; Nathaniel Hudson; Ryan Chard; André Bauer 001; Ian T. Foster; Kyle Chard (SC Workshops, 2023)

Searching for the Ground Truth: Assessing the Similarity of Benchmarking Runs. - André Bauer 001; Martin Straesser; Mark Leznik; Lukas Beierlieb; Marius Hadry; Nathaniel Hudson; Kyle Chard; Samuel Kounev; Ian T. Foster (ICPE (Companion), 2023)

Efficient Data Processing: Assessing the Performance of Different Programming Languages. - Lukas Beierlieb; André Bauer 001; Robert Leppich; Lukas Iffländer; Samuel Kounev (ICPE (Companion), 2023)

Autoscaler Evaluation and Configuration: A Practitioner's Guideline. - Martin Straesser; Simon Eismann; Jóakim von Kistowski; André Bauer 001; Samuel Kounev (ICPE, 2023)

A Systematic Approach for Benchmarking of Container Orchestration Frameworks. - Martin Straesser; Jonas Mathiasch; André Bauer 001; Samuel Kounev (ICPE, 2023)

Telescope: An Automated Hybrid Forecasting Approach on a Level-Playing Field. - André Bauer 001; Mark Leznik; Michael Stenger; Robert Leppich; Nikolas Herbst; Samuel Kounev; Ian T. Foster (CoRR, 2023)

Attention Lens: A Tool for Mechanistically Interpreting the Attention Head Information Retrieval Mechanism. - Mansi Sakarvadia; Arham Khan; Aswathy Ajith; Daniel Grzenda; Nathaniel Hudson; André Bauer 001; Kyle Chard; Ian T. Foster (CoRR, 2023)

An Empirical Study of Container Image Configurations and Their Impact on Start Times (Container Image Data). - Martin Straesser; André Bauer 001; Robert Leppich; Nikolas Herbst; Kyle Chard; Ian T. Foster; Samuel Kounev (Zenodo, 2023)

A Systematic Approach for Benchmarking of Container Orchestration Frameworks (Research Paper Artifact). - Martin Straesser; Jonas Mathiasch; André Bauer 001; Samuel Kounev (Zenodo, 2023)

A literature review of IoT and CPS - What they are, and what they are not. - Veronika Lesch; Marwin Züfle; André Bauer 001; Lukas Iffländer; Christian Krupitzer; Samuel Kounev (J. Syst. Softw., 2023)

Recommendation of secure group communication schemes using multi-objective optimization. - Thomas Prantl; André Bauer 001; Lukas Iffländer; Christian Krupitzer; Samuel Kounev (Int. J. Inf. Sec., 2023)

Security Analysis of a Decentralized, Revocable and Verifiable Attribute-Based Encryption Scheme. - Thomas Prantl; Marco Lauer; Lukas Horn; Simon Engel; David Dingel; André Bauer 001; Christian Krupitzer; Samuel Kounev (ARES, 2024)

An Empirical Investigation of Container Building Strategies and Warm Times to Reduce Cold Starts in Scientific Computing Serverless Functions. - André Bauer 001; Maxime Gonthier; Haochen Pan; Ryan Chard; Daniel Grzenda; Martin Straesser; J. Gregory Pauloski; Alok Kamatar; Matt Baughman; Nathaniel Hudson; Ian T. Foster; Kyle Chard (e-Science, 2024)

Enhancing Energy Efficiency with Multi-Site Scheduling Strategies. - Alok Kamatar; Valérie Hayot-Sasson; Yadu N. Babuji; André Bauer 001; Gourav Rattihalli; Ninad Hogade; Dejan S. Milojicic; Kyle Chard; Ian T. Foster (IPDPS (Workshops), 2024)

Octopus: Experiences with a Hybrid Event-Driven Architecture for Distributed Scientific Computing. - Haochen Pan; Ryan Chard; Sicheng Zhou; Alok Kamatar; Rafael Vescovi; Valérie Hayot-Sasson; André Bauer 001; Maxime Gonthier; Kyle Chard; Ian T. Foster (SC Workshops, 2024)

Unveiling Temporal Performance Deviation: Leveraging Clustering in Microservices Performance Analysis. - André Bauer 001; Timo Dittus; Martin Straesser; Alok Kamatar; Matt Baughman; Lukas Beierlieb; Marius Hadry; Daniel Grillmeyer; Yannik Lubas; Samuel Kounev; Ian T. Foster; Kyle Chard (ICPE (Companion), 2024)

Comprehensive Exploration of Synthetic Data Generation: A Survey. - André Bauer 001; Simon Trapp; Michael Stenger; Robert Leppich; Samuel Kounev; Mark Leznik; Kyle Chard; Ian T. Foster (CoRR, 2024)

Oil & Water? Diffusion of AI Within and Across Scientific Fields. - Eamon Duede; William B. Dolan; André Bauer 001; Ian T. Foster; Karim R. Lakhani (CoRR, 2024)

GreenFaaS: Maximizing Energy Efficiency of HPC Workloads with FaaS. - Alok Kamatar; Valérie Hayot-Sasson; Yadu N. Babuji; André Bauer 001; Gourav Rattihalli; Ninad Hogade; Dejan S. Milojicic; Kyle Chard; Ian T. Foster (CoRR, 2024)

The globus compute dataset: An open function-as-a-service dataset from the edge to the cloud. - André Bauer 001; Haochen Pan; Ryan Chard; Yadu N. Babuji; Josh Bryan; Devesh Tiwari; Ian T. Foster; Kyle Chard (Future Gener. Comput. Syst., 2024)

De Bello Homomorphico: Investigation of the extensibility of the OpenFHE library with basic mathematical functions by means of common approaches using the example of the CKKS cryptosystem. - Thomas Prantl; Lukas Horn; Simon Engel; Lukas Iffländer; Lukas Beierlieb; Christian Krupitzer; André Bauer 001; Mansi Sakarvadia; Ian T. Foster; Samuel Kounev (Int. J. Inf. Sec., 2024)

Thinking in Categories: A Survey on Assessing the Quality for Time Series Synthesis. - Michael Stenger; André Bauer 001; Thomas Prantl; Robert Leppich; Nathaniel Hudson; Kyle Chard; Ian T. Foster; Samuel Kounev (ACM J. Data Inf. Qual., 2024)

Evaluation is key: a survey on evaluation measures for synthetic time series. - Michael Stenger; Robert Leppich; Ian T. Foster; Samuel Kounev; André Bauer 001 (J. Big Data, 2024)

Quantifying Data Leakage in Failure Prediction Tasks. - Daniel Grillmeyer; Marius Hadry; Veronika Lesch; Vanessa Borst; Robert Leppich; André Bauer 001; Samuel Kounev (ICPE, 2025)

Generating Executable Microservice Applications for Performance Benchmarking. - Yannik Lubas; Martin Straesser; André Bauer 001; Samuel Kounev (ICPE, 2025)

Microservice Applications and Their Workloads on GitHub. - Yannik Lubas; Martin Straesser; Ivo Rohwer; Samuel Kounev; André Bauer 001 (ICPE (Companion), 2025)

Bridging Clusters: A Comparative Look at Multi-Cluster Networking Performance in Kubernetes. - Sai Sindhur Malleni; Raul Sevilla Canavate; José Castillo Lema; André Bauer 001 (ICPE, 2025)

HotCloudPerf'25 Workshop Chairs' Welcome. - Klervie Toczé; André Bauer 001; Dragi Kimovski; Daniele Bonetta (ICPE (Companion), 2025)

Quo Vadis CKKS: Comparison of the realization of basic mathematical functions for the homomorphic cryptosystem CKKS using De Bello and polynomial approximations. - Thomas Prantl; Lukas Horn; Simon Engel; André Bauer 001; Samuel Kounev (J. Inf. Secur. Appl., 2025)

Generating Executable Microservices for Performance Benchmarking (Research Paper Artifact). - Yannik Lubas; Martin Straesser; André Bauer 001; Samuel Kounev (Zenodo, 2025)

Core Hours and Carbon Credits: Incentivizing Sustainability in HPC. - Alok Kamatar; Maxime Gonthier; Valérie Hayot-Sasson; André Bauer 001; Marcin Copik; Torsten Hoefler; Raul Castro Fernandez; Kyle Chard; Ian T. Foster (CoRR, 2025)

Object Proxy Patterns for Accelerating Distributed Applications. - J. Gregory Pauloski; Valérie Hayot-Sasson; Logan T. Ward; Alexander Brace; André Bauer 001; Kyle Chard; Ian T. Foster (IEEE Trans. Parallel Distributed Syst., 2025)

Quantifying Data Leakage in Failure Prediction Tasks. - Daniel Grillmeyer; Veronika Lesch; Marius Hadry; Vanessa Borst; Robert Leppich; André Bauer 001; Samuel Kounev (Zenodo, 2025)

STEB: In Search of the Best Evaluation Approach for Synthetic Time Series. - Michael Stenger; Robert Leppich; André Bauer 001; Samuel Kounev (CoRR, 2025)

Telling fortunes? Evaluation of traffic forecasting models using traffic and context features. - Marius Hadry; André Bauer 001; Robert Leppich; Veronika Lesch; Samuel Kounev (Appl. Intell., 2025)

Decomposing the Time Series Forecasting Pipeline: A Modular Approach for Time Series Representation, Information Extraction, and Projection. - Robert Leppich; Michael Stenger; André Bauer 001; Samuel Kounev (CoRR, 2025)