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Adaptive Resource Management (ARM)

Lupe

One of the areas we work on in the DOS group is adaptive resource management for data-intensive distributed applications, aiming at systems that automatically adapt to workloads and environments. Learn more...

Team

Lupe

Research

Aiming to make it easier to run data-intensive applications efficiently on distributed computing infrastructures from small devices to large-scale clusters, we work on adaptive resource management, following an iterative systems research approach.

Current research directions include:

Recent Publications

Scheinert, Dominik and Thamsen, Lauritz and Zhu, Houkun and Will, Jonathan and Acker, Alexander and Wittkopp, Thorsten and Kao, Odej (2021). Bellamy: Reusing Performance Models for Distributed Dataflow Jobs Across Contexts. 2021 IEEE International Conference on Cluster Computing (CLUSTER). IEEE, 261-270.


Ulf Leser, Odej Kao, and others (2021). The Collaborative Research Center FONDA. Datenbank Spektrum. Springer.


Gontarska, Kordian and Wrazen, Weronika and Beilharz, Jossekin and Schmid, Robert and Thamsen, Lauritz and Polze, Andreas (2021). Predicting Medical Interventions from Vital Parameters: Towards a Decision Support System for Remote Patient Monitoring. 19th Conference on Artificial Intelligence in Medicine (AIME'21), 293-297.


Zusatzinformationen / Extras

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Contact

Lauritz Thamsen
+49 30 314-24539
TEL
Room 1210