piwik-script

Intern
    Chair of Computer Science II - Software Engineering

    LIMBO

    LIMBO Load Intensity Modeling Tool

    LIMBO is an Eclipse-based tool for handling and instantiating load intensity models based on the Descartes Load Intensity Model (DLIM). LIMBO users can define variable arrival rates for a multitude of purposes, such as custom request time-stamp generation for benchmarking or the re-parametrization of request traces. LIMBO offers an accessible way of editing DLIM instances and extracting them from existing traces. It also supports additional modeling utilities, such as using high level - DLIM (hl-DLIM) parameters for easy creation of new DLIM instances through a model creation wizard.

    Links:

    If you have any questions, please contact Jóakim v. Kistowski.


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    Publications

    2019[ to top ]
    • {Chameleon: A Hybrid, Proactive Auto-Scaling Mechanism on a Level-Playing Field}. A. Bauer; N. Herbst; S. Spinner; A. Ali-Eldin; S. Kounev; in IEEE Transactions on Parallel and Distributed Systems (2019). 30(4) 800–813.
    • {Methoden und Messverfahren f{\"u}r Automatisches Skalieren in Elastischen Cloud Umgebungen}. N. Herbst; (2019, Juni).
    • Measuring, Rating, and Predicting the Energy Efficiency of Servers. J. von Kistowski; Thesis; University of W{\"u}rzburg, Germany. (2019, März).
    2018[ to top ]
    • Methods and Benchmarks for Auto-Scaling Mechanisms in Elastic Cloud Environments. N. Herbst; Thesis; University of W{\"u}rzburg, Germany. (2018, Juli).
    • {How we built a scalable micro-service application - The Tea Store}. N. Herbst; (2018, Juli).
    2017[ to top ]
    • {Runtime Prediction of Power Consumption for Server Reconfigurations}. M. Deffner; Thesis; University of W{\"u}rzburg; Am Hubland, Informatikgeb{\"a}ude, 97074 W{\"u}rzburg, Germany. (2017, Mai).
    • {Design and Evaluation of a Proactive, Application-Aware Auto-Scaler}. A. Bauer; N. Herbst; S. Kounev; in {Proceedings of the 8th ACM/SPEC International Conference on Performance Engineering (ICPE 2017)} (2017).
    • {Modeling and Extracting Load Intensity Profiles}. J. von Kistowski; N. Herbst; S. Kounev; H. Groenda; C. Stier; S. Lehrig; in ACM Transactions on Autonomous and Adaptive Systems (TAAS) (2017). 11(4) 23:1–23:28.
    2015[ to top ]
    • {BUNGEE: An Elasticity Benchmark for Self-Adaptive IaaS Cloud Environments}. N. R. Herbst; S. Kounev; A. Weber; H. Groenda; in Proceedings of the 10th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 2015) (2015).
    • {Modeling and Extracting Load Intensity Profiles}. J. von Kistowski; N. R. Herbst; D. Zoller; S. Kounev; A. Hotho; in Proceedings of the 10th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 2015) (2015).
    2014[ to top ]
    • {Resource Elasticity Benchmarking in Cloud Environments}. A. Weber; Thesis; {Karlsruhe Institute of Technology (KIT)}; Am Fasanengarten 5, 76131 Karlsruhe, Germany. (2014, August).
    • {Towards a Resource Elasticity Benchmark for Cloud Environments}. A. Weber; N. R. Herbst; H. Groenda; S. Kounev; in Proceedings of the 2nd International Workshop on Hot Topics in Cloud Service Scalability (HotTopiCS 2014), co-located with the 5th ACM/SPEC International Conference on Performance Engineering (ICPE 2014) (2014). 5:1–5:8.
    • {LIMBO - A Load Intensity Modeling Platform}. J. von Kistowski; (2014, März).
    • {Using and Extending LIMBO for the Descriptive Modeling of Arrival Behaviors}. J. von Kistowski; N. R. Herbst; S. Kounev; in Proceedings of the Symposium on Software Performance 2014 (2014). 131–140.
    • {LIMBO: A Tool For Modeling Variable Load Intensities}. J. von Kistowski; N. R. Herbst; S. Kounev; in Proceedings of the 5th ACM/SPEC International Conference on Performance Engineering (ICPE 2014) (2014). 225–226.
    • {Modeling Variations in Load Intensity over Time}. J. von Kistowski; N. R. Herbst; S. Kounev; in Proceedings of the 3rd International Workshop on Large-Scale Testing (LT 2014), co-located with the 5th ACM/SPEC International Conference on Performance Engineering (ICPE 2014) (2014). 1–4.