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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

Gontarska, Kordian and Geldenhuys, Morgan and Scheinert, Dominik and Wiesner, Philipp and Polze, Andreas and Thamsen, Lauritz (2021). Evaluation of Load Prediction Techniques for Distributed Stream Processing. International Conference on Cloud Engineering. IEEE, 91-98.


Pfister, Benjamin JJ and Lickefett, Wolf S and Nitschke, Jan and Paul, Sumit and Geldenhuys, Morgan K and Scheinert, Dominik and Gontarska, Kordian and Thamsen, Lauritz (2021). Rafiki: Task-level Capacity Planning in Distributed Stream Processing Systems. International European Conference on Parallel and Distributed Computing. Springer, to appear.


Geldenhuys, Morgan K. and Will, Jonathan and Pfister, Benjamin and Haug, Martin and Scharmann, Alexander and Thamsen, Lauritz (2021). Dependable IoT Data Stream Processing for Monitoring and Control of Urban Infrastructures. IEEE International Conference on Cloud Engineering. IEEE, 244-250.


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Contact

Lauritz Thamsen
+49 30 314-24539
TEL
Room 1210