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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]

Geldenhuys, Morgan and Thamsen, Lauritz and Kao, Odej (2020). Chiron: Optimizing Fault Tolerance in QoS-aware Distributed Stream Processing Jobs [37]. 2020 IEEE International Conference on Big Data, 434–440.


Will, Jonathan and Bader, Jonathan and Thamsen, Lauritz (2020). Towards Collaborative Optimization of Cluster Configurations for Distributed Dataflow Jobs [38]. 2020 IEEE International Conference on Big Data. IEEE, 2851–2856.


Behnke, Ilja and Pirl, Lukas and Thamsen, Lauritz and Danicki, Robert and Polze, Andreas and Kao, Odej (2020). Interrupting Real-Time IoT Tasks: How Bad Can It Be to Connect Your Critical Embedded System to the Internet? [39]. IPCCC 2020: 39th International Performance Computing and Communications Conference, 1-6.


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

Contact

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