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

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 [11]
  • Scheduling of Data Processing Jobs [12]
  • Auto-Tuning of Scalable Systems [13]
  • Dependable IoT Systems [14]

Recent Publications

<< previous [15]
next >> [36]

Bader, Jonathan and Lehmann, Fabian and Groth, Alexander and Thamsen, Lauritz and Scheinert, Dominik and Will, Jonathan and Leser, Ulf and Kao, Odej (2022). Reshi: Recommending Resources for Scientific Workflow Tasks on Heterogeneous Infrastructures [40]. 41th International Performance Computing and Communications Conference 2022. IEEE, to appear.


Will, Jonathan and Thamsen, Lauritz and Bader, Jonathan and Scheinert, Dominik and Kao, Odej (2022). Ruya: Memory-Aware Iterative Optimization of Cluster Configurations for Big Data Processing [41]. IEEE International Conference on Big Data (BigData). IEEE, to appear.


Scheinert, Dominik and Becker, Soeren and Bader, Jonathan and Thamsen, Lauritz and Will, Jonathan and Kao, Odej (2022). Perona: Robust Infrastructure Fingerprinting for Resource-Efficient Big Data Analytics [42]. IEEE International Conference on Big Data (BigData). IEEE, to appear.


<< previous [43]
next >> [64]

Contact

Lauritz Thamsen
+49 30 314-24539
TEL
Room 1210
e-mail query [65]
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