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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

Felgentreff, Tim and Lincke, Jens and Hirschfeld, Robert and Thamsen, Lauritz (2015). Lively Groups: Shared Behavior in a World of Objects without Classes or Prototypes. In Proceedings of the Future Programming Workshop (FPW) 2015, co-located with the Conference on Object-oriented Programming, Systems, Languages, and Applications (OOPSLA). ACM, 15–22.


Renner, Thomas and Thamsen, Lauritz and Kao, Odej (2015). Network-Aware Resource Management for Scalable Data Analytics Frameworks. Proceedings of the 1st First Workshop on Data-Centric Infrastructure for Big Data Science (DIBS), co-located with the 2015 IEEE International Conference on BigData. IEEE, 2793–2800.


Thamsen, Lauritz and Steinert, Bastian and Hirschfeld, Robert (2015). Preserving Access to Previous System States in the Lively Kernel. Design Thinking Research. Springer, 235–264.


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Contact

Lauritz Thamsen
+49 30 314-24539
TEL
Room 1210