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Adaptive Resource Management (ARM)

Lupe [1]

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... [2]

Team

Lupe [3]

Lauritz [4], Morgan [5], Ilja [6], Kordian [7], Dominik [8], Philipp [9], Jonathan B. [10], and Jonathan W. [11]

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:

  • Resource Allocation for Distributed Processing [12]
  • Scheduling of Data Processing Jobs [13]
  • Auto-Tuning of Scalable Systems [14]
  • Dependable IoT Systems [15]

Recent Publications

<< previous [16]
next >> [33]

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.


Gontarska, Kordian and Geldenhuys, Morgan and Scheinert, Dominik and Wiesner, Philipp and Polze, Andreas and Thamsen, Lauritz (2021). Evaluation of Load Prediction Techniques for Distributed Stream Processing [37]. International Conference on Cloud Engineering. IEEE, 91-98.


Pfister, Benjamin JJ and Lickefett, Wolf S and Nitschke, Jan and Paul, Sumit and Geldenhuys, Morgan K and Scheinert, Dominik and Gontarska, Kordian and Thamsen, Lauritz (2021). Rafiki: Task-level Capacity Planning in Distributed Stream Processing Systems [38]. International European Conference on Parallel and Distributed Computing. Springer, to appear.


<< previous [39]
next >> [56]

Contact

Lauritz Thamsen
+49 30 314-24539
TEL
Room 1210
e-mail query [57]
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