Подписаться
Johannes Grohmann
Johannes Grohmann
WhatsApp (Meta)
Подтвержден адрес электронной почты в домене meta.com - Главная страница
Название
Процитировано
Процитировано
Год
Teastore: A micro-service reference application for benchmarking, modeling and resource management research
J Von Kistowski, S Eismann, N Schmitt, A Bauer, J Grohmann, S Kounev
2018 IEEE 26th International Symposium on Modeling, Analysis, and Simulation …, 2018
125*2018
Serverless applications: Why, when, and how?
S Eismann, J Scheuner, E Van Eyk, M Schwinger, J Grohmann, N Herbst, ...
IEEE Software 38 (1), 32-39, 2020
1052020
A SPEC RG cloud group's vision on the performance challenges of FaaS cloud architectures
E Van Eyk, A Iosup, CL Abad, J Grohmann, S Eismann
Companion of the 2018 acm/spec international conference on performance …, 2018
942018
How is performance addressed in DevOps?
CP Bezemer, S Eismann, V Ferme, J Grohmann, R Heinrich, P Jamshidi, ...
Proceedings of the 2019 ACM/SPEC International Conference on Performance …, 2019
752019
A review of serverless use cases and their characteristics
S Eismann, J Scheuner, E Van Eyk, M Schwinger, J Grohmann, N Herbst, ...
arXiv preprint arXiv:2008.11110, 2020
632020
The SPEC-RG reference architecture for FaaS: From microservices and containers to serverless platforms
E Van Eyk, J Grohmann, S Eismann, A Bauer, L Versluis, L Toader, ...
IEEE Internet Computing 23 (6), 7-18, 2019
552019
The state of serverless applications: Collection, characterization, and community consensus
S Eismann, J Scheuner, E Van Eyk, M Schwinger, J Grohmann, N Herbst, ...
IEEE Transactions on Software Engineering 48 (10), 4152-4166, 2021
512021
On learning in collective self-adaptive systems: state of practice and a 3d framework
M D'Angelo, S Gerasimou, S Ghahremani, J Grohmann, I Nunes, ...
2019 IEEE/ACM 14th International Symposium on Software Engineering for …, 2019
512019
Predicting the costs of serverless workflows
S Eismann, J Grohmann, E Van Eyk, N Herbst, S Kounev
Proceedings of the ACM/SPEC international conference on performance …, 2020
462020
Sizeless: Predicting the optimal size of serverless functions
S Eismann, L Bui, J Grohmann, C Abad, N Herbst, S Kounev
Proceedings of the 22nd International Middleware Conference, 248-259, 2021
442021
Monitorless: Predicting performance degradation in cloud applications with machine learning
J Grohmann, PK Nicholson, JO Iglesias, S Kounev, D Lugones
Proceedings of the 20th international middleware conference, 149-162, 2019
262019
On the value of service demand estimation for auto-scaling
A Bauer, J Grohmann, N Herbst, S Kounev
Measurement, Modelling and Evaluation of Computing Systems: 19th …, 2018
222018
An automated forecasting framework based on method recommendation for seasonal time series
A Bauer, M Züfle, J Grohmann, N Schmitt, N Herbst, S Kounev
Proceedings of the ACM/SPEC International Conference on Performance …, 2020
192020
Online model learning for self-aware computing infrastructures
S Spinner, J Grohmann, S Eismann, S Kounev
Journal of Systems and Software 147, 1-16, 2019
182019
Detecting Parametric Dependencies for Performance Models Using Feature Selection Techniques
J Grohmann, S Eismann, S Elflein, M Mazkatli, J Kistowski, S Kounev
2019 IEEE 27th International Symposium on Modeling, Analysis, and Simulation …, 2019
142019
Self-tuning resource demand estimation
J Grohmann, N Herbst, S Spinner, S Kounev
2017 IEEE International Conference on Autonomic Computing (ICAC), 21-26, 2017
142017
Incremental calibration of architectural performance models with parametric dependencies
M Mazkatli, D Monschein, J Grohmann, A Koziolek
2020 IEEE International Conference on Software Architecture (ICSA), 23-34, 2020
132020
Black-box Learning of Parametric Dependencies for Performance Models
V Ackermann, J Grohmann, S Eismann, S Kounev
13th International Workshop on Models@run.time (MRT), 2018
132018
Sarde: A framework for continuous and self-adaptive resource demand estimation
J Grohmann, S Eismann, A Bauer, S Spinner, J Blum, N Herbst, S Kounev
ACM Transactions on Autonomous and Adaptive Systems (TAAS) 15 (2), 1-31, 2021
122021
To fail or not to fail: Predicting hard disk drive failure time windows
M Züfle, C Krupitzer, F Erhard, J Grohmann, S Kounev
Measurement, Modelling and Evaluation of Computing Systems: 20th …, 2020
122020
В данный момент система не может выполнить эту операцию. Повторите попытку позднее.
Статьи 1–20