TU Berlin

Department of Telecommunication SystemsAdaptive Resource Management

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Adaptive Resource Management (ARM)


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...


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

Lauritz Thamsen, Jossekin Beilharz, Vinh Thuy Tran, Sasho Nedelkoski, and Odej Kao (2020). Mary, Hugo, and Hugo*: Learning to Schedule Distributed Data-Parallel Processing Jobs on Shared Clusters. Concurrency and Computation: Practice and Experience. Wiley, e5823.

Will, Jonathan and Arslan, Onur and Bader, Jonathan and Scheinert, Dominik and Thamsen, Lauritz (2021). Training Data Reduction for Performance Models of Data Analytics Jobs in the Cloud. International Conference on Big Data. IEEE, to appear.

Tilcher, David Konstantin and Popescu, Florin and Sommer, Harald and Thamsen, Lauritz and Thamsen, Paul Uwe (2021). Control Optimization Through Prediction-Based Wastewater Management. Proceedings of the ASME 2021 Fluids Engineering Division Summer Meeting. ASME, 9.


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