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Energy Efficiency of Hierarchical Server Load Distribution Strategies.

, , , , , and . MASCOTS, page 75-84. IEEE Computer Society, (2015)

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Common Errors and Assumptions in Energy Measurement and Management. Technical Talk at Symposium on Software Performance (SSP) 2015, (November 2015)Detecting Parametric Dependencies for Performance Models Using Feature Selection Techniques., , , , , and . MASCOTS, page 309-322. IEEE Computer Society, (2019)Scenario-based Resilience Evaluation and Improvement of Microservice Architectures: An Experience Report., , , , , and . ECSA (Companion), volume 2978 of CEUR Workshop Proceedings, CEUR-WS.org, (2021)Measuring, Rating, and Predicting the Energy Efficiency of Servers (Messung, Bewertung und Vorhersage von Serverenergieeffizienz). Würzburg University, Germany, (2019)base-search.net (ftunivwuerz:oai:opus.bibliothek.uni-wuerzburg.de:17847).Energy Benchmarking., and . Encyclopedia of Big Data Technologies, Springer, (2019)Measuring, Rating, and Predicting the Energy Efficiency of Servers. University of Würzburg, Germany, (March 2019)TeaStore - A Micro-Service Application for Benchmarking, Modeling and Resource Management Research. Talk at Workshop on Hot Topics in Cloud Computing Performance 2018, (April 2018)Modeling Variations in Load Intensity Profiles. Karlsruhe Institute of Technology (KIT), Am Fasanengarten 5, 76131 Karlsruhe, Germany, Master Thesis, (March 2014)<b>Gesellschaft zur Förderung des Forschungstransfers (GFFT) Prize "Best Master Thesis"</b>.TeaStore: A Micro-Service Reference Application for Cloud Researchers., , , , , , and . UCC Companion, page 11-12. IEEE, (2018)TeaStore - A Micro-Service Reference Application for Performance Engineers., , , , , and . ICPE Companion, page 47-48. ACM, (2019)