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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.


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.


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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Contact

Lauritz Thamsen
+49 30 314-24539
TEL
Room 1210