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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

Wiesner, Philipp and Behnke, Ilja and Scheinert, Dominik and Gontarska, Kordian and Thamsen, Lauritz (2021). Let's Wait Awhile: How Temporal Workload Shifting Can Reduce Carbon Emissions in the Cloud. 22nd International Middleware Conference (Middleware). ACM, to appear.

Siling Chen, Florian Brokhausen, Philipp Wiesner, Lauritz Thamsen, and Andrea Cominola (2021). Assessing the Resilience of Water Distribution Networks Under Different Sensor Network Architectures and Data Sampling Frequencies. Proceedings of the 2nd International Symposium on Water System Operations (ISWSO). IAHR, 1-2.

David Bermbach, Abhishek Chandra, Chandra Krintz, Aniruddha Gokhale, Aleksander Slominski, Lauritz Thamsen, Everton Cavalcante, Tian Guo, Ivona Brandic, and Rich Wolski (2021). On the Future of Cloud Engineering. Proceedings of the 9th IEEE International Conference on Cloud Engineering (IC2E). IEEE, 264-275.

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Lauritz Thamsen
+49 30 314-24539
Room 1210