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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

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.

Lorenz, Felix and Geldenhuys, Morgan and Sommer, Harald and Jakobs, Frauke and L├╝ring, Carsten and Skwarek, Volker and Behnke, Ilja and Thamsen, Lauritz (2020). A Scalable and Dependable Data Analytics Platform for Water Infrastructure Monitoring. 2020 IEEE International Conference on Big Data. IEEE, 3488–3493.

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.

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Lauritz Thamsen
+49 30 314-24539
Room 1210