Prof. Sergei Gorlatch

University of Muenster, Germany



Sergei Gorlatch has been Full Professor of Computer Science at the University of Muenster (Germany) since 2003. Earlier he was Associate Professor at the Technical University of Berlin, Assistant Professor at the University of Passau, and Humboldt Research Fellow at the Technical University of Munich, all in Germany. His research interests include algorithms, software, and applications for high-performance parallel and distributed systems. Prof. Gorlatch has more than 200 peer-reviewed publications in refereed international books, journals, and conferences. Among his recent achievements at top conferences are the following: the paper at the ACM ICFP was recognized as an ACM SIGPLAN Research Highlight 2021 with a publication in the Communications of the ACM; the paper presented at the ACM/IEEE CGO 2018  was prized with the Best Paper Award of the conference. Sergei Gorlatch holds MSc degree in Applied Mathematics and Computer Science from the National State University of Ukraine in Kiev, PhD degree in Computer Science from the Institute of Cybernetics of the Ukrainian Academy of Sciences, and Habilitation degree in Computer Science from the University of Passau in Germany.

Speech Title:  Improving the Quality of Service in IoT by Software-Defined Networking

Abstract:: This talk deals with one of the most important challenges in the Internet of Things (IoT) applications – ensuring a high level of Quality of Service (QoS) for the users. The variety of IoT applications makes use of the newest achievements in modern computer science including 5G networks, Artificial Intelligence (AI), distributed and Cloud computing, etc. We describe our recent research on the methods and tools for developing modern IoT applications with a guaranteed level of QoS. Our special focus is on using the emerging technology of Software-Defined Networking (SDN) for challenging classes of IoT applications including online games, alarm systems, etc. We report experimental results that confirm the advantages of our approach compared to the state of the art.