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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 Wrazen, Weronika and Beilharz, Jossekin and Schmid, Robert and Thamsen, Lauritz and Polze, Andreas (2021). Predicting Medical Interventions from Vital Parameters: Towards a Decision Support System for Remote Patient Monitoring. 19th Conference on Artificial Intelligence in Medicine (AIME'21), 293-297.


Danicki, Robert and Haug, Martin and Behnke, Ilja and Mädje, Laurenz and Thamsen, Lauritz (2021). Detecting and Mitigating Network Packet Overloads on Real-Time Devices in IoT Systems. 4th International Workshop on Edge Systems, Analytics and Networking (EdgeSys'21), 25-30.


Will, Jonathan and Thamsen, Lauritz and Scheinert, Dominik and Bader, Jonathan and Kao, Odej (2021). C3O: Collaborative Cluster Configuration Optimization for Distributed Data Processing in Public Clouds. International Conference on Cloud Engineering. IEEE, 43-52.


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Contact

Lauritz Thamsen
+49 30 314-24539
TEL
Room 1210