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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]


Lupe [3]

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


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

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Martin Haug, Felix Lorenz, and Lauritz Thamsen (2021). GRAL: Localization of Floating Wireless Sensors in Pipe Networks. Proceedings of the 9th IEEE International Conference on Cloud Engineering (IC2E). IEEE, 251-257.

Ilja Behnke, Philipp Wiesner, Robert Danicki, and Lauritz Thamsen (2022). A Priority-Aware Multiqueue NIC Design for Real-Time IoT Devices [37]. The 37th ACM/SIGAPP Symposium on Applied Computing (SAC '22). ACM, To appear.

Thamsen, Lauritz and Gulenko, Anton and Perscheid, Michael and Krahn, Robert and Hirschfeld, Robert and Thomas, David A. (2012). Orca: A Single-Language Web Framework for Collaborative Development [38]. Proceedings of the 2012 10th International Conference on Creating, Connecting and Collaborating Through Computing. IEEE Computer Society, 45–52.

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