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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...

Team

Lupe

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

Bermbach, David and Bader, Jonathan and Hasenburg, Jonathan and Pfandzelter, Tobias and Thamsen, Lauritz (2021). AuctionWhisk: Using an Auction-Inspired Approach for Function Placement in Serverless Fog Platforms. Software: Practice and Experience. Wiley, to appear.


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.


Scheinert, Dominik and Zhu, Houkun and Thamsen, Lauritz and Geldenhuys, Morgan K. and Will, Jonathan and Acker, Alexander and Kao, Odej (2021). Enel: Context-Aware Dynamic Scaling of Distributed Dataflow Jobs using Graph Propagation. 40th IEEE International Performance Computing and Communications Conference. IEEE, 1-8.


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Contact

Lauritz Thamsen
+49 30 314-24539
TEL
1210