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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]

Lorenz, Felix and Thamsen, Lauritz and Wilke, Andreas and Behnke, Ilja and Waldmüller-Littke, Jens and Komarov, Ilya and Kao, Odej and Paeschke, Manfred (2020). Fingerprinting Analog IoT Sensors for Secret-Free Authentication [37]. 2020 29th International Conference on Computer Communications and Networks (ICCCN). IEEE, 1–6.


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? [38]. IPCCC 2020: 39th International Performance Computing and Communications Conference, 1-6.


Lorenz, Felix and Geldenhuys, Morgan and Sommer, Harald and Jakobs, Frauke and Lüring, Carsten and Skwarek, Volker and Behnke, Ilja and Thamsen, Lauritz (2020). A Scalable and Dependable Data Analytics Platform for Water Infrastructure Monitoring [39]. 2020 IEEE International Conference on Big Data. IEEE, 3488–3493.


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

Contact

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