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).
Ankit Chaudhary, Jeyhun Karimov, Steffen Zeuch, Volker Markl
Incremental Stream Query Merging
David Burrell, Xenofon Chatziliadis, Eleni Tzirita Zacharatou, Steffen Zeuch, Volker Markl
Workload Prediction for IoT Data Management Systems
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
Clemens Lutz, Sebastian Breß, Steffen Zeuch, Tilmann Rabl, Volker Markl
Triton Join: Efficiently Scaling to a Large Join State on GPUs with Fast Interconnects
Bonaventura Del Monte, Steffen Zeuch, Tilmann Rabl, Volker Markl
Rethinking Stateful Stream Processing with RDMA
BIFOLD welcomes the first six Junior Fellows
The Berlin Institute for the Foundations of Learning and Data is very pleased to announce the first six BIFOLD Junior Fellows. They were selected for the excellence of their research and are already well-established researchers in the computer sciences. In addition, their research interests show exceptional potential for BIFOLD’s research goals, either by combining machine learning and data management or by bridging the two disciplines and other research areas. The first six Junior Fellows will cover a broad range of research topics during their collaboration with BIFOLD.
New BIFOLD research groups established
The Berlin Institute for the Foundations of Learning and Data (BIFOLD) set up two new Research Training Groups, led by Dr. Stefan Chmiela and Dr. Steffen Zeuch. The goal of these new research units at BIFOLD is to enable a junior researcher to conduct independent research and prepare him for a leadership position. Initial funding includes their own position as well as two PhD students and/or research associates for three years.
TU Berlin and DFKI database systems researchers offer multiple presentations at VLDB 2020
Researchers at TU Berlin Database Systems and Information Management (DIMA) group and Intelligent Analytics for Massive Data (IAM) group at DFKI presented one full paper, one demo paper and three PhD thesis papers at the 46th International Conference on Very Large Databases (VLDB 2020).
Research Group Lead
Doctoral Researcher
Doctoral Researcher