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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

Thamsen, Lauritz and Scheinert, Dominik and Will, Jonathan and Bader, Jonathan and Kao, Odej (2022). Collaborative Cluster Configuration for Distributed Data-Parallel Processing: A Research Overview. Datenbank-Spektrum. Springer.


Steinert, Bastian and Thamsen, Lauritz and Felgentreff, Tim and Hirschfeld, Robert (2014). Object Versioning to Support Recovery Needs: Using Proxies to Preserve Previous Development States in Lively. Proceedings of the 10th ACM Symposium on Dynamic Languages. ACM, 113–124.


Siling Chen, Florian Brokhausen, Philipp Wiesner, Lauritz Thamsen, and Andrea Cominola (2021). Assessing the Resilience of Water Distribution Networks Under Different Sensor Network Architectures and Data Sampling Frequencies. Proceedings of the 2nd International Symposium on Water System Operations (ISWSO). IAHR, 1-2.


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Contact

Lauritz Thamsen
+49 30 314-24539
TEL
1210