I’m interested in building communication systems with provable performance. To this end, I use methods and techniques from stochastic modelling and optimization such as Queuing Theory and Network Calculus. Recently, I have been working on the optimization and inference-based control of adaptive communication systems within the collaborative research center MAKI. My work is related to the application fields of Software-defined Networking, Multimedia and Caching.
Dynamic Adaptive Streaming over HTTP (DASH) aims to constantly provide high user quality of experience in dynamically changing network environments. The heterogeneity of the streaming environment makes many of the developed DASH algorithms possess performance affinities that we denote as sweet spots. In this work we show the substantial impact of the video player choice and its configuration on the streaming performance.
Blockchain based Distributed Applications
Current Blockchain generations go far beyond transactions to enable distributed applications and smart contracts. In this work, we look at smart contract applications that eliminate brokers, e.g., in supply chains, Internet-of-Things (IoT) applications, communication networks and energy markets.
Athene Young Investigator Award „Stochastic Methods for the Analysis of Parallelized Communication Systems“
This Athene Young Investigator award supports a research plan to develop performance evaluation methods for parallelized communication systems under synchronization constraints.
Modern communication networks rely heavily on parallel multi-server systems, e.g., for multipath transmission protocols, web server farms, networked high performance computing systems, as well as, real-time data analytics. These systems exploit parallelization to provide lower latency, capacity scalability and higher reliability. Although accurate performance models for parallel communication systems are essential to guide the architectural design of the future Internet, understanding the performance properties of such systems remains, however, notoriously hard. A particular difficulty arises since such systems naturally comprise synchronization events due to the intrinsic modes of operation of many protocols and applications – take for example the result aggregation in big data analysis systems such as MapReduce /Hadoop or the in-order output of Multipath TCP.
The work within this project builds on the frameworks of queuing theory and stochastic network calculus to provide stochastic bounds on the performance of parallelized systems in terms of throughput and delay distributions. The methods developed here will enable analytical investigations of network protocols and applications that actively control multi-server architectures under synchronization. The developed models will directly contribute to the optimization of applications such as adaptive, multipath-aware video streaming algorithms, as well as, into the design of scheduling and routing algorithms for future Internet architectures.
H-probe: active probing for estimating traffic correlations
H-probe enables researchers to estimate cross-traffic correlations along network paths using active probes.