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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

Will, Jonathan and Thamsen, Lauritz and Bader, Jonathan and Scheinert, Dominik and Kao, Odej (2022). Ruya: Memory-Aware Iterative Optimization of Cluster Configurations for Big Data Processing. IEEE International Conference on Big Data (BigData). IEEE, to appear.


Scheinert, Dominik and Becker, Soeren and Bader, Jonathan and Thamsen, Lauritz and Will, Jonathan and Kao, Odej (2022). Perona: Robust Infrastructure Fingerprinting for Resource-Efficient Big Data Analytics. IEEE International Conference on Big Data (BigData). IEEE, to appear.


Scheinert, Dominik and Aghdam, Babak Sistani Zadeh and Becker, Soeren and Kao, Odej and Thamsen, Lauritz (2022). Probabilistic Time Series Forecasting for Adaptive Monitoring in Edge Computing Environments. IEEE International Conference on Big Data (BigData). IEEE, to appear.


Zusatzinformationen / Extras

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Contact

Lauritz Thamsen
+49 30 314-24539
TEL
Room 1210