Publications
Peer Reviewed Journal and Magazine Articles
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Thinking in Categories: A Survey on Assessing the Quality for Time Series Synthesis. in J. Data and Information Quality (2024). 16(2) Association for Computing Machinery, New York, NY, USA.
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Benchmarking of Secure Group Communication schemes with Focus on IoT. in Discover Data (2024). 2(1) Springer Science and Business Media LLC.
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Evaluation is key: a survey on evaluation measures for synthetic time series. in Journal of Big Data (2024). 11 66.
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Comprehensive Exploration of Synthetic Data Generation: A Survey. in arXiv preprint (2024). 103.https://doi.org/10.48550/arXiv.2401.02524
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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. in International Journal of Information Security (2023).
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Towards a Cryptography Encyclopedia: A Survey on Attribute-Based Encryption. in Journal of Surveillance, Security and Safety (2023).
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Recommendation of Secure Group Communication Schemes using Multi Objective Optimization. in International Journal of Information Security (2023).
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Telescope: An Automated Hybrid Forecasting Approach on a Level-Playing Field. (2023).
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A literature review of IoT and CPS—What they are, and what they are not. in Journal of Systems and Software (2023). 111631. Elsevier.
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A Survey on Secure Group Communication Schemes with Focus on IoT Communication. in IEEE Access (2022). IEEE.Accepted but not yet published
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Towards Forecasting Future Snow Cover Dynamics in the European Alps - The Potential of Long Optical Remote-Sensing Time Series. in Remote Sensing (2022). 14(18)
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Artificial Intelligence-Based Early Detection Of Acute Kidney Injury After Cardiac Surgery. in European Journal of Cardio-Thoracic Surgery (2022).Joint first authorship; To be published soon
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SARDE: A Framework for Continuous and Self-Adaptive Resource Demand Estimation. in ACM Transactions on Autonomous and Adaptive Systems (2021). 15(2) Association for Computing Machinery, New York, NY, USA.
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{Time Series Forecasting for Self-Aware Systems}. in Proceedings of the IEEE (2020). 108(7) 1068–1093.
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The SPEC-RG Reference Architecture for FaaS: From Microservices and Containers to Serverless Platforms. in IEEE Internet Computing (2019). 23(6) 7–18. IEEE.
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Methodological Principles for Reproducible Performance Evaluation in Cloud Computing. in IEEE Transactions on Software Engineering (2019). 47(8) 1528–1543.
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{Modeling of Aggregated IoT Traffic and Its Application to an IoT Cloud}. in Proceedings of the IEEE (2019). 107(4) 679–694.
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{Chameleon: A Hybrid, Proactive Auto-Scaling Mechanism on a Level-Playing Field}. in IEEE Transactions on Parallel and Distributed Systems (2019). 30(4) 800–813. IEEE.
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{Quantifying Cloud Performance and Dependability: Taxonomy, Metric Design, and Emerging Challenges}. in ACM Transactions on Modeling and Performance Evaluation of Computing Systems (ToMPECS) (2018). 3(4) 19:1–19:36. ACM, New York, NY, USA.
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An Experimental Performance Evaluation of Autoscalers for Complex Workflows. in ACM Transactions on Modeling and Performance Evaluation of Computing Systems (ToMPECS) (2018). 3(2) 8:1–8:32. ACM, New York, NY, USA.
Peer Reviewed Full Conference Papers
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Security Analysis of a Decentralized, Revocable and Verifiable Attribute-Based Encryption Scheme. in Proceedings of the 19th International Conference on Availability, Reliability and Security (2024). ACM.
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An Empirical Investigation of Container Building Strategies and Warm Times to Reduce Cold Starts in Scientific Computing Serverless Functions. in 2024 IEEE 20th International Conference on e-Science (e-Science) (2024).
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An Empirical Study of Container Image Configurations and Their Impact on Start Times. in 2023 IEEE/ACM 23rd International Symposium on Cluster, Cloud and Internet Computing (CCGrid) (2023). 94–105. IEEE.
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Autoscaler Evaluation and Configuration: A Practitioner’s Guideline. in Proceedings of the 2023 ACM/SPEC International Conference on Performance Engineering (2023). 31–41. Association for Computing Machinery, New York, NY, USA.
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A Systematic Approach for Benchmarking of Container Orchestration Frameworks. in Proceedings of the 2023 ACM/SPEC International Conference on Performance Engineering (2023). 187–198. Association for Computing Machinery, New York, NY, USA.
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Why Is It Not Solved Yet? Challenges for Production-Ready Autoscaling. in Proceedings of the 2022 ACM/SPEC on International Conference on Performance Engineering (2022). 105–115. Association for Computing Machinery, New York, NY, USA.
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Libra: A Benchmark for Time Series Forecasting Methods. in Proceedings of the 12th ACM/SPEC International Conference on Performance Engineering (ICPE) (2021). ACM, New York, NY, USA.
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Benchmarking of Pre- and Post-Quantum Group Encryption Schemes with Focus on IoT. in 2021 IEEE 40th International Performance Computing and Communications Conference (IPCCC) (2021).
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Kaa: Evaluating Elasticity of Cloud-hosted DBMS. in Proceedings of the 11th IEEE International Conference on Cloud Computing (CloudCom) (2019).
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Chamulteon: Coordinated Auto-Scaling of Micro-Services. in Proceedings of the 39th IEEE International Conference on Distributed Computing Systems (ICDCS) (2019).
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Online Power Consumption Estimation for Functions in Cloud Applications. in Proceedings of the 16th IEEE International Conference on Autonomic Computing (ICAC) (2019). IEEE.
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{Autonomic Forecasting Method Selection: Examination and Ways Ahead}. in Proceedings of the 16th {IEEE} International Conference on Autonomic Computing (ICAC) (2019). IEEE.
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{TeaStore: A Micro-Service Reference Application for Benchmarking, Modeling and Resource Management Research}. in Proceedings of the 26th IEEE International Symposium on the Modelling, Analysis, and Simulation of Computer and Telecommunication Systems (2018). 223–236. IEEE Computer Society.{Acceptance Rate: 29.5\% (23/78)}
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{FOX: Cost-Awareness for Autonomic Resource Management in Public Clouds}. in Proceedings of the 9th ACM/SPEC International Conference on Performance Engineering (ICPE 2018) (2018). ACM, New York, NY, USA.Full Paper Acceptance Ratio: 23,7%
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{On the Value of Service Demand Estimation for Auto-Scaling}. in Proceedings of 19th International GI/ITG Conference on Measurement, Modelling and Evaluation of Computing Systems (MMB 2018) (2018). (Vol. 10740) 142–156. Springer, Cham.
Peer Reviewed Short Conference Papers
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Unveiling Temporal Performance Deviation: Leveraging Clustering in Microservices Performance Analysis. in Companion of the 15th ACM/SPEC International Conference on Performance Engineering (2024). 72–76. Association for Computing Machinery, New York, NY, USA.
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Performance Impact Analysis of Homomorphic Encryption: A Case Study Using Linear Regression as an Example. in Information Security Practice and Experience, W. Meng, Z. Yan, V. Piuri (eds.) (2023). 284–298. Springer Nature Singapore, Singapore.
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Searching for the Ground Truth: Assessing the Similarity of Benchmarking Runs. in Companion of the 2023 ACM/SPEC International Conference on Performance Engineering (2023). 95–99. Association for Computing Machinery, New York, NY, USA.
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Change Point Detection for MongoDB Time Series Performance Regression. in Proceedings of the 2022 ACM/SPEC on International Conference on Performance Engineering (2022). ACM.
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Automated Triage of Performance Change Points Using Time Series Analysis and Machine Learning. in Proceedings of the 2022 ACM/SPEC on International Conference on Performance Engineering (2022). ACM.
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Same, Same, but Dissimilar: Exploring Measurements for Workload Time-Series Similarity. in Proceedings of the 2022 ACM/SPEC on International Conference on Performance Engineering (2022). 89–96. Association for Computing Machinery, New York, NY, USA.
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Telescope: An Automatic Feature Extraction and Transformation Approach for Time Series Forecasting on a Level-Playing Field. in Proceedings of the 36th International Conference on Data Engineering (ICDE) (2020).
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{An Automated Forecasting Framework based on Method Recommendation for Seasonal Time Series}. in Proceedings of the ACM/SPEC International Conference on Performance Engineering (2020). 48–55. Association for Computing Machinery (ACM), New York, NY, USA.
PhD Thesis
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Automated Hybrid Time Series Forecasting: Design, Benchmarking, and Use Cases. (2021). Universit{ä}t W{ü}rzburg.
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Automated Hybrid Time Series Forecasting: Design, Benchmarking, and Use Cases. (2020, December). University of W{ü}rzburg, Germany.{Distinction, SPEC Kaivalya Dixit Distinguished Dissertation Award 2021}
Book Chapters
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Automatisierte Hybride Zeitreihenprognose. in Ausgezeichnete Informatikdissertationen 2020, S. Hölldobler (ed.) (2021). 29–38. Gesellschaft für Informatik e.V., Bonn.
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{Elasticity of Cloud Platforms}. in {Systems Benchmarking: For Scientists and Engineers}, S. Kounev, K.-D. Lange, J. von Kistowski (eds.) (2020). 319–340. Springer.
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{Challenges and Approaches: Forecasting for Autonomic Computing}. in {Organic Computing: Doctoral Dissertation Colloquium 2018}, S. Tomforde, B. Sick (eds.) (2019). kassel university press GmbH.
Peer Reviewed Workshop Papers
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An Experience Report on the Suitability of a Distributed Group Encryption Scheme for an IoT Use Case. in 2022 IEEE 95th Vehicular Technology Conference (VTC2022) (2022). IEEE.
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{Systematic Search for Optimal Resource Configurations of Distributed Applications}. in 2019 IEEE 4th International Workshops on Foundations and Applications of Self* Systems (FAS*W) (2019). 120–125. IEEE Computer Society, Los Alamitos, CA, USA.
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{Utilizing Clustering to Optimize Resource Demand Estimation Approaches}. in 2019 IEEE 4th International Workshops on Foundations and Applications of Self* Systems (FAS*W) (2019). 134–139. IEEE.
Peer Reviewed Extended Abstracts
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{Towards Splitting Monolithic Workflows into Serverless Functions and Estimating Their Run-Time in the Earth Observation Domain}. in Proceedings of the 12th Symposium on Software Performance (SSP) (2021).Extended Abstract
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{Methodological Principles for Reproducible Performance Evaluation in Cloud Computing}. in Software Engineering 2020, Fachtagung des GI-Fachbereichs Softwaretechnik, 24.-28. Februar 2020, Innsbruck, Austria, M. Felderer, W. Hasselbring, R. Rabiser, R. Jung (eds.) (2020). (Vol. {P-300}) 93–94. Gesellschaft f{{ü}}r Informatik e.V.
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{Telescope: A Hybrid Forecast Method for Univariate Time Series}. in {Proceedings of the International work-conference on Time Series (ITISE 2017)} (2017).
Peer Reviewed Poster Papers
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SPEC Research - Introducing the Predictive Data Analytics Working Group. in Companion of the 2022 ACM/SPEC on International Conference on Performance Engineering (2022).
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SPEC Research - Introducing the Predictive Data Analytics Working Group. in Companion of the 2022 ACM/SPEC International Conference on Performance Engineering (2022).
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TeaStore: A Micro-Service Reference Application for Cloud Researchers. in Proceedings of 2018 IEEE/ACM International Conference on Utility and Cloud Computing Companion (UCC Companion) (2018). 11–12. IEEE.
Peer Reviewed Tutorial Papers
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{Best Practices for Time Series Forecasting}. in {2019 IEEE 4th International Workshops on Foundations and Applications of Self* Systems (FAS*W)} (2019).
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{Design and Evaluation of a Proactive, Application-Aware Auto-Scaler}. in {Proceedings of the 8th ACM/SPEC International Conference on Performance Engineering (ICPE 2017)} (2017).
Techreports
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{Methodological Principles for Reproducible Performance Evaluation in Cloud Computing - A SPEC Research Technical Report}. (SPEC-RG-2019-04), (2019). SPEC Research Group --- Cloud Working Group, Standard Performance Evaluation Corporation (SPEC).
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Performance-feedback autoscaling with budget constraints for cloud-based workloads of workflows. in arXiv preprint arXiv:1905.10270 (2019).
Newsletter
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SPEC Research Group Newsletter, Issue 12. (2023, April).Published by Standard Performance Evaluation Corporation (SPEC)
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SPEC Research Group Newsletter, Issue 11. (2022, April).Published by Standard Performance Evaluation Corporation (SPEC)
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{SPEC Research Group Newsletter, vol. 3 no. 2}. (2021, April).Published by Standard Performance Evaluation Corporation (SPEC)
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{SPEC Research Group Newsletter, vol. 3 no. 1}. (2020, April).Published by Standard Performance Evaluation Corporation (SPEC)
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{SPEC Research Group Newsletter, vol. 2 no. 4}. (2019, April).Published by Standard Performance Evaluation Corporation (SPEC)
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{SPEC Research Group Newsletter, vol. 2 no. 3}. (2018, April).Published by Standard Performance Evaluation Corporation (SPEC)
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{SPEC Research Group Newsletter, vol. 2 no. 2}. (2017, April).Published by Standard Performance Evaluation Corporation (SPEC)
Talks
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{Chameleon: A Hybrid, Proactive Auto-Scaling Mechanism on a Level-Playing Field}. (2019, June).
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{Extending BUNGEE Elasticity Benchmark for Multi-Tier Cloud Applications}. (2018, April).
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{Design and Evaluation of a Proactive, Application-Aware Elasticity Mechanism}. (2016, November).
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{Chameleon: Design and Evaluation of a Proactive, Application-Aware Elasticity Mechanism}. (2016, October).
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