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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]

Scheinert, Dominik and Thamsen, Lauritz and Zhu, Houkun and Will, Jonathan and Acker, Alexander and Wittkopp, Thorsten and Kao, Odej (2021). Bellamy: Reusing Performance Models for Distributed Dataflow Jobs Across Contexts [37]. 2021 IEEE International Conference on Cluster Computing (CLUSTER). IEEE, 261-270.


Ulf Leser, Odej Kao, and others (2021). The Collaborative Research Center FONDA [38]. Datenbank Spektrum. Springer.


Gontarska, Kordian and Wrazen, Weronika and Beilharz, Jossekin and Schmid, Robert and Thamsen, Lauritz and Polze, Andreas (2021). Predicting Medical Interventions from Vital Parameters: Towards a Decision Support System for Remote Patient Monitoring [39]. 19th Conference on Artificial Intelligence in Medicine (AIME'21), 293-297.


<< previous [40]
next >> [57]

Contact

Lauritz Thamsen
+49 30 314-24539
TEL
Room 1210
e-mail query [58]
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