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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...

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

Geldenhuys, Morgan and Thamsen, Lauritz and Kao, Odej (2020). Chiron: Optimizing Fault Tolerance in QoS-aware Distributed Stream Processing Jobs. 2020 IEEE International Conference on Big Data, 434–440.


Will, Jonathan and Bader, Jonathan and Thamsen, Lauritz (2020). Towards Collaborative Optimization of Cluster Configurations for Distributed Dataflow Jobs. 2020 IEEE International Conference on Big Data. IEEE, 2851–2856.


Behnke, Ilja and Pirl, Lukas and Thamsen, Lauritz and Danicki, Robert and Polze, Andreas and Kao, Odej (2020). Interrupting Real-Time IoT Tasks: How Bad Can It Be to Connect Your Critical Embedded System to the Internet?. IPCCC 2020: 39th International Performance Computing and Communications Conference, 1-6.


Zusatzinformationen / Extras

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Contact

Lauritz Thamsen
+49 30 314-24539
TEL
Room 1210