Dependable IoT Systems

As a result of the many technical advances in microcomputers and mobile connectivity, large numbers of sensor-equipped devices and distributed systems are used for the continuous monitoring and control of smart factories, cities, and homes. However, operating these systems in the geo-distributed, heterogeneous, and dynamic computing environments of the Internet of Things (IoT) so that they meet given performance and dependability requirements is often difficult. For this, an effective and reliable resource management is essential. In addition, these IoT systems need to be tested adequately. We, therefore, investigate new methods and systems that support the continuous operation and testing of IoT systems.

Ongoing Research

We currently work on multiple topics in this area:

• Meeting Real-Time Requirements on Industrial IoT Devices, where we detect and mitigate network-generated interrupt floods on critical embedded IoT systems.
• Testing and Simulation Tools for Internet of Things Systems, where we design novel testing tools and simulators to assess the behavior of distributed systems in the distributed computing environments of the Internet of Things.

Featured Publications

• A priority-aware multiqueue nic design for real-time iot devices.
  Ilja Behnke, Philipp Wiesner, Robert Danicki, and Lauritz Thamsen.
  In Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing. ACM. 2022. [arXiv preprint]
• Dependable IoT Data Stream Processing for Monitoring and Control of Urban Infrastructures
  Morgan Geldenhuys, Jonathan Will, Benjamin Pfister, Martin Haug, Alex Scharmann, and Lauritz Thamsen
  In the Proceedings of the 9th IEEE International Conference on Cloud Engineering (IC2E). To be presented at the First International Workshop on Testing Distributed Internet of Things Systems (TDIS). IEEE. 2021. [arXiv preprint] [code]
• LEAF: Simulating Large Energy-Aware Fog Computing Environments.
  Philipp Wiesner and Lauritz Thamsen.
  In the Proceedings of the 2021 IEEE 5th International Conference on Fog and Edge Computing (ICFEC). IEEE. 2021. [arXiv preprint] [video] [code]