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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

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.


Thamsen, Lauritz and Verbitskiy, Ilya and Rabier, Benjamin and Kao, Odej (2018). Learning Efficient Co-locations for Scheduling Distributed Dataflows in Shared Clusters. Services Transactions on Big Data. Services Society, 1–15.


Ulf Leser, Odej Kao, and others (2021). The Collaborative Research Center FONDA. Datenbank Spektrum. Springer.


Zusatzinformationen / Extras

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Contact

Lauritz Thamsen
+49 30 314-24539
TEL
Room 1210