Distributed Data Stream Processing in Heterogeneous Environments
Heterogeneous data streams, Distributed fog and edge environments, IoT data and application management
Dr. Steffen Zeuch and his Research Training Group concentrate on developing a data management system for the processing of heterogeneous data streams in distributed fog and edge environments. An explosion in both the number and types of connected devices will create novel data-driven applications in the near future. These applications require low-latency, location awareness, wide-spread geographical distribution, and real-time data processing on potentially millions of distributed data sources and potentially millions of simultaneous data processing operations. In some cases these applications have to operate under tight resource constraints with respect to bandwidth, processing power, and energy consumption. The aim is to design a data management system that unifies cloud, fog and sensor environments at an unprecedented scale. This system should host these environments on a unified platform and leverage the opportunities of the unified architecture for cross-paradigm data processing optimizations, to support emerging IoT applications. In order to achieve that, they will collaborate with the members of BIFOLD’Data and Application Management for the Internet of Things Lab (IoT-Lab).
Bonaventura Del Monte, Steffen Zeuch, Tilmann Rabl, Volker Markl
Rethinking Stateful Stream Processing with RDMA
Clemens Lutz, Sebastian Breß, Steffen Zeuch, Tilmann Rabl, Volker Markl
Triton Join: Efficiently Scaling the Operator State on GPUs with Fast Interconnects
Steffen Zeuch, Xenofon Chatziliadis, Ankit Chaudhary, Dimitrios Giouroukis, Philipp M. Grulich, Dwi Prasetyo Adi Nugroho, Ariane Ziehn, Volker Markl
NebulaStream: Data Management for the Internet of Things
Ariane Ziehn, Christian Mandel, Kathrin Stich, Rolf Dembinski, Karin Hochbaum, Steffen Zeuch, Volker Markl
IoT-PMA: Patient Health Monitoring in Medical IoT Ecosystems
Clemens Lutz, Sebastian Breß, Steffen Zeuch, Tilmann Rabl, Volker Markl
Triton Join: Efficiently Scaling to a Large Join State on GPUs with Fast Interconnects
Research Group Lead
Doctoral Researcher
Doctoral Researcher