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TU Berlin

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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 Renner, Thomas and Byfeld, Marvin and Paeschke, Markus and Schröder, Daniel and Böhm, Felix (2016). Visually Programming Dataflows for Distributed Data Analytics. In the Proceedings of the 2016 IEEE International Conference on Big Data (BigData). IEEE, 2276–2285.


Verbitskiy, Ilya and Thamsen, Lauritz and Kao, Odej (2016). When to Use a Distributed Dataflow Engine: Evaluating the Performance of Apache Flink. In the Proceedings of the 2nd IEEE International Conference on Cloud and Big Data Computing (CBDCom). IEEE, 698–705.


Thamsen, Lauritz and Renner, Thomas and Kao, Odej (2016). Continuously Improving the Resource Utilization of Iterative Parallel Dataflows. In the Proceedings of the IEEE International Conference on Distributed Computing Systems Workshops (ICDCSW). IEEE, 1–6.


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Contact

Lauritz Thamsen
+49 30 314-24539
TEL
1210