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Samuel Kounev
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Publications
- 2023
- [j53]Samuel Kounev, Nikolas Herbst, Cristina L. Abad, Alexandru Iosup, Ian T. Foster, Prashant J. Shenoy, Omer F. Rana, Andrew A. Chien:
Serverless Computing: What It Is, and What It Is Not? Commun. ACM 66(9): 80-92 (2023) - [c203]Martin Straesser, André Bauer, Robert Leppich, Nikolas Herbst, Kyle Chard, Ian T. Foster, Samuel Kounev:
An Empirical Study of Container Image Configurations and Their Impact on Start Times. CCGrid 2023: 94-105 - [d1]Martin Straesser, André Bauer, Robert Leppich, Nikolas Herbst, Kyle Chard, Ian T. Foster, Samuel Kounev:
An Empirical Study of Container Image Configurations and Their Impact on Start Times (Container Image Data). Zenodo, 2023 - [i15]André Bauer, Mark Leznik, Michael Stenger, Robert Leppich, Nikolas Herbst, Samuel Kounev, Ian T. Foster:
Telescope: An Automated Hybrid Forecasting Approach on a Level-Playing Field. CoRR abs/2309.15871 (2023) - 2021
- [j41]Johannes Grohmann, Simon Eismann, André Bauer, Simon Spinner, Johannes Blum, Nikolas Herbst, Samuel Kounev:
SARDE: A Framework for Continuous and Self-Adaptive Resource Demand Estimation. ACM Trans. Auton. Adapt. Syst. 15(2): 6:1-6:31 (2021) - [c168]Simon Eismann, Long Bui, Johannes Grohmann, Cristina L. Abad, Nikolas Herbst, Samuel Kounev:
Sizeless: predicting the optimal size of serverless functions. Middleware 2021: 248-259 - [c163]Johannes Grohmann, Martin Straesser, Avi Chalbani, Simon Eismann, Yair Arian, Nikolas Herbst, Noam Peretz, Samuel Kounev:
SuanMing: Explainable Prediction of Performance Degradations in Microservice Applications. ICPE 2021: 165-176 - [c159]André Bauer, Marwin Züfle, Simon Eismann, Johannes Grohmann, Nikolas Herbst, Samuel Kounev:
Libra: A Benchmark for Time Series Forecasting Methods. ICPE 2021: 189-200 - 2020
- [j39]Johannes Grohmann, Nikolas Herbst, Avi Chalbani, Yair Arian, Noam Peretz, Samuel Kounev:
A Taxonomy of Techniques for SLO Failure Prediction in Software Systems. Comput. 9(1): 10 (2020) - [j38]André Bauer, Marwin Züfle, Nikolas Herbst, Albin Zehe, Andreas Hotho, Samuel Kounev:
Time Series Forecasting for Self-Aware Systems. Proc. IEEE 108(7): 1068-1093 (2020) - [c151]André Bauer, Marwin Züfle, Nikolas Herbst, Samuel Kounev, Valentin Curtef:
Telescope: An Automatic Feature Extraction and Transformation Approach for Time Series Forecasting on a Level-Playing Field. ICDE 2020: 1902-1905 - [c142]André Bauer, Marwin Züfle, Johannes Grohmann, Norbert Schmitt, Nikolas Herbst, Samuel Kounev:
An Automated Forecasting Framework based on Method Recommendation for Seasonal Time Series. ICPE 2020: 48-55 - [c141]Simon Eismann, Johannes Grohmann, Erwin Van Eyk, Nikolas Herbst, Samuel Kounev:
Predicting the Costs of Serverless Workflows. ICPE 2020: 265-276 - [i7]Simon Eismann, Long Bui, Johannes Grohmann, Cristina L. Abad, Nikolas Herbst, Samuel Kounev:
Sizeless: Predicting the optimal size of serverless functions. CoRR abs/2010.15162 (2020) - 2019
- [j29]André Bauer, Nikolas Herbst, Simon Spinner, Ahmed Ali-Eldin, Samuel Kounev:
Chameleon: A Hybrid, Proactive Auto-Scaling Mechanism on a Level-Playing Field. IEEE Trans. Parallel Distributed Syst. 30(4): 800-813 (2019) - [c139]Marwin Züfle, André Bauer, Veronika Lesch, Christian Krupitzer, Nikolas Herbst, Samuel Kounev, Valentin Curtef:
Autonomic Forecasting Method Selection: Examination and Ways Ahead. ICAC 2019: 167-176 - [c138]André Bauer, Veronika Lesch, Laurens Versluis, Alexey Ilyushkin, Nikolas Herbst, Samuel Kounev:
Chamulteon: Coordinated Auto-Scaling of Micro-Services. ICDCS 2019: 2015-2025 - [c132]André Bauer, Simon Eismann, Johannes Grohmann, Nikolas Herbst, Samuel Kounev:
Systematic Search for Optimal Resource Configurations of Distributed Applications. FAS*W@SASO/ICAC 2019: 120-125 - [c131]Johannes Grohmann, Simon Eismann, André Bauer, Marwin Züfle, Nikolas Herbst, Samuel Kounev:
Utilizing Clustering to Optimize Resource Demand Estimation Approaches. FAS*W@SASO/ICAC 2019: 134-139 - [c130]André Bauer, Marwin Züfle, Nikolas Herbst, Samuel Kounev:
Best Practices for Time Series Forecasting (Tutorial). FAS*W@SASO/ICAC 2019: 255-256 - 2018
- [j27]Nikolas Herbst, André Bauer, Samuel Kounev, Giorgos Oikonomou, Erwin Van Eyk, George Kousiouris, Athanasia Evangelinou, Rouven Krebs, Tim Brecht, Cristina L. Abad, Alexandru Iosup:
Quantifying Cloud Performance and Dependability: Taxonomy, Metric Design, and Emerging Challenges. ACM Trans. Model. Perform. Evaluation Comput. Syst. 3(4): 19:1-19:36 (2018) - [c122]Johannes Grohmann, Nikolas Herbst, Simon Spinner, Samuel Kounev:
Using Machine Learning for Recommending Service Demand Estimation Approaches - Position Paper. CLOSER 2018: 473-480 - [c117]André Bauer, Johannes Grohmann, Nikolas Herbst, Samuel Kounev:
On the Value of Service Demand Estimation for Auto-scaling. MMB 2018: 142-156 - [c115]Simon Eismann, Jóakim von Kistowski, Johannes Grohmann, André Bauer, Norbert Schmitt, Nikolas Herbst, Samuel Kounev:
TeaStore: A Micro-Service Reference Application for Cloud Researchers. UCC Companion 2018: 11-12 - [c113]Veronika Lesch, André Bauer, Nikolas Herbst, Samuel Kounev:
FOX: Cost-Awareness for Autonomic Resource Management in Public Clouds. ICPE 2018: 4-15 - 2017
- [j24]Jóakim von Kistowski, Nikolas Herbst, Samuel Kounev, Henning Groenda, Christian Stier, Sebastian Lehrig:
Modeling and Extracting Load Intensity Profiles. ACM Trans. Auton. Adapt. Syst. 11(4): 23:1-23:28 (2017) - [c110]Johannes Grohmann, Nikolas Herbst, Simon Spinner, Samuel Kounev:
Self-Tuning Resource Demand Estimation. ICAC 2017: 21-26 - [c100]André Bauer, Nikolas Herbst, Samuel Kounev:
Design and Evaluation of a Proactive, Application-Aware Auto-Scaler: Tutorial Paper. ICPE 2017: 425-428 - [p12]Nikolas Herbst, Steffen Becker, Samuel Kounev, Heiko Koziolek, Martina Maggio, Aleksandar Milenkoski, Evgenia Smirni:
Metrics and Benchmarks for Self-aware Computing Systems. Self-Aware Computing Systems 2017: 437-464 - [p9]Nikolas Herbst, Ayman A. Amin, Artur Andrzejak, Lars Grunske, Samuel Kounev, Ole J. Mengshoel, Priya Krishnan Sundararajan:
Online Workload Forecasting. Self-Aware Computing Systems 2017: 529-553 - 2016
- [i5]Nikolas Herbst, Rouven Krebs, Giorgos Oikonomou, George Kousiouris, Athanasia Evangelinou, Alexandru Iosup, Samuel Kounev:
Ready for Rain? A View from SPEC Research on the Future of Cloud Metrics. CoRR abs/1604.03470 (2016) - 2015
- [c87]Simon Spinner, Nikolas Herbst, Samuel Kounev, Xiaoyun Zhu, Lei Lu, Mustafa Uysal, Rean Griffith:
Proactive Memory Scaling of Virtualized Applications. CLOUD 2015: 277-284 - [c84]Nikolas Roman Herbst, Samuel Kounev, Andreas Weber, Henning Groenda:
BUNGEE: An Elasticity Benchmark for Self-Adaptive IaaS Cloud Environments. SEAMS@ICSE 2015: 46-56 - [c83]Jóakim von Kistowski, Nikolas Herbst, Daniel Zoller, Samuel Kounev, Andreas Hotho:
Modeling and Extracting Load Intensity Profiles. SEAMS@ICSE 2015: 109-119 - 2014
- [j14]Nikolas Roman Herbst, Nikolaus Huber, Samuel Kounev, Erich Amrehn:
Self-adaptive workload classification and forecasting for proactive resource provisioning. Concurr. Comput. Pract. Exp. 26(12): 2053-2078 (2014) - [c66]Jóakim von Kistowski, Nikolas Herbst, Samuel Kounev:
Using and Extending LIMBO for the Descriptive Modeling of Arrival Behaviors. SoSP 2014: 131-140 - [c62]Jóakim von Kistowski, Nikolas Roman Herbst, Samuel Kounev:
Modeling variations in load intensity over time. LT@ICPE 2014: 1-4 - [c61]Andreas Weber, Nikolas Herbst, Henning Groenda, Samuel Kounev:
Towards a Resource Elasticity Benchmark for Cloud Environments. HotTopiCS@ICPE 2014: 5:1-5:8 - [c59]Jóakim von Kistowski, Nikolas Herbst, Samuel Kounev:
LIMBO: a tool for modeling variable load intensities. ICPE 2014: 225-226 - 2013
- [c56]Nikolas Roman Herbst, Samuel Kounev, Ralf H. Reussner:
Elasticity in Cloud Computing: What It Is, and What It Is Not. ICAC 2013: 23-27 - [c48]Nikolas Roman Herbst, Nikolaus Huber, Samuel Kounev, Erich Amrehn:
Self-adaptive workload classification and forecasting for proactive resource provisioning. ICPE 2013: 187-198
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