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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 >> [35]

Franz Bender, Jan Jonas Brune, Nick Lauritz Keutel, Ilja Behnke and Lauritz Thamsen (2021). PIERES: A Playground for Network Interrupt Experiments on Real-Time Embedded Systems in the IoT [39]. 2021 ACM/SPEC International Conference on Performance Engineering Companion. ACM, 81-84.


Danicki, Robert and Haug, Martin and Behnke, Ilja and Mädje, Laurenz and Thamsen, Lauritz (2021). Detecting and Mitigating Network Packet Overloads on Real-Time Devices in IoT Systems [40]. 4th International Workshop on Edge Systems, Analytics and Networking (EdgeSys'21), 25-30.


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 [41]. 19th Conference on Artificial Intelligence in Medicine (AIME'21), 293-297.


<< previous [42]
next >> [62]

Contact

Lauritz Thamsen
+49 30 314-24539
TEL
1210
Contact [63]
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