Distributed systems and parallel computing

With increasing connectivity, digitization, and data intensity, the demands on distributed and parallel computing systems in companies and organizations are growing. The efficient processing of large amounts of data in real time, the flexible scaling of resources, and the assurance of performance and energy efficiency are key challenges that conventional IT infrastructures are often unable to meet.

Our research area develops innovative approaches for the edge-cloud continuum that enable seamless distribution and processing of data and workloads across different locations and infrastructures. The focus is on dynamic resource management, energy-efficient parallelization, the development of scalable architectures for industrial applications, and the integration of AI and data management tools into distributed systems. We support companies in implementing modern, distributed systems that enable flexible and efficient use of computing resources while reducing operating costs. Our research includes the development of new algorithms, frameworks, and tools for the management and optimization of distributed systems, the performance of performance analyses, and the support of pilot projects in various industries. Through practical research and close cooperation with partners from industry and academia, we contribute to making digital infrastructures future-proof, sustainable, and powerful.

Our solutions enable companies to fully exploit the potential of digitalization, implement innovative data-driven business models, and position themselves successfully in the competitive environment. The results of our work show that the use of modern distributed systems can significantly improve scalability, reliability, and energy efficiency.

Our research projects are developed in close collaboration with industry partners. They are market- and demand-oriented, with the aim of providing applicable solutions for the cloud edge ecosystem.

We develop distributed systems for optimizing production processes and increasing scalability in manufacturing.

Research question: How can distributed architectures efficiently collect, process, and utilize production data?

Example: Implementation of a distributed system for real-time monitoring and control of manufacturing processes.

We develop energy-saving solutions and measurement systems for energy consumption in edge cloud environments.

Research question: How can energy consumption in distributed IT infrastructures be transparently recorded and optimized?

Example: Development of a measurement system for continuous monitoring and optimization of energy consumption in edge cloud environments.