Model-based Analysis of Next-Generation Networks


It is foreseen, that new paradigms in computer networking like Network Function Virtualization (NFV), Network Virtualization (NV) and Software Defined Networking (SDN), will increase the flexibility and openness of modern communication infrastructure. The new approaches will enable virtualization of network functions (NFV), network slicing (NV) and a (logically) centralized control of the network (SDN), such that functionality can be implemented in a physically decoupled way, e.g. running in a data center. SDN enables novel approaches to analyze and control the traffic in the network, however, requiring a deep understanding of the underlying hardware. While the packet processing pipeline of well-designed, specialized hardware is specified in detail, virtualized software on commodity hardware is more difficult to tackle. On the other hand, the additional degrees of freedom enabled by virtualizing network functions (NFV), such as custom packet processing pipelines and dynamic placement, create new possibilities for optimization.

This project aims to evaluate, combine, and enhance performance models of networks and their components concerned with packet processing. The performance assessment of novel networks requires suitable modeling tools, e.g. to represent interaction on the control plane or take software-based packet processing into account. New models are also required to account for changes in the networking hardware that describe the effects of limiting factors like CPU interconnects or the bandwidth of memory, PCIe, or Ethernet. We aim to combine models, that describe individual effects, into larger entities that allow the modeling of complex packet processing tasks.

ModANet covers various methods for performance analysis, e.g. resource-based models, models based on Network Calculus, and simulations. We plan to build a framework for model evaluation, which allows for automated determination of the quality and scope of models, thus enables covering a large parameter space. We plan to automate the calibration and evaluation of the analyzed models using machine learning techniques. We also aim to evaluate the modeling approaches with regard to their complexity to obtain feasible models.

The outcomes of the project should provide a deep understanding of the characteristics of the different processing pipelines in SDN-based networks. Considering separate packet processing steps in network nodes allows to make reliable statements about the performance of composed packet processing chains. Furthermore, the enhanced configuration possibilities lead to new optimizations.


Finished student theses

Author Title Type Advisors Year Links
Alexander Frank Evaluation and Analysis of a Hardware Programmable High-Performance Switch MA Dominik Scholz, Sebastian Gallenmüller, Henning Stubbe 2019 Pdf
Felix Hartmond Network Device Benchmarking with an 100Gb/s SDN Router MA Dominik Scholz, Sebastian Gallenmüller, Henning Stubbe 2019 Pdf
Stefan Stark A Framework for Analysis of Network Performance Metrics MA Dominik Scholz, Sebastian Gallenmüller 2019 Pdf
Marcel Mussner Comparing Network Calculus Guarantees with Latency Measurements in Emulated Networks BA Max Helm, Dominik Scholz, Benedikt Jaeger, Henning Stubbe 2019 Pdf
Henning Stubbe Performance Analysis of P4 on NetFPGA MA Dominik Scholz, Sebastian Gallenmüller, Fabien Geyer 2018 Pdf
Oliver Schmidt A Framework for In-band Network Telemetry using P4 GR Dominik Scholz, Sebastian Gallenmüller, Fabien Geyer 2018 Pdf
Burak Atalay A Framework for Automated Analysis of P4Runtime MA Dominik Scholz, Fabien Geyer, Sebastian Gallenmüller 2018 Pdf
Henning Stubbe Implementing a P4 Benchmarking Suite for libmoon IDP Sebastian Gallenmüller, Dominik Scholz, Fabien Geyer 2017 Pdf
Oliver Schmidt P4: A Programming Language for Packet Processing BA Sebastian Gallenmüller, Dominik Scholz 2016 Pdf

Open and running student theses

Author Title Type Advisors Year Links
Ivan Kendzor Modeling Scheduling Algorithms in Network Calculus BA Max Helm, Henning Stubbe, Dominik Scholz, Fabien Geyer 2019 Pdf
Maximilian Endraß Performance Evaluation of Software Dataplanes MA Dominik Scholz, Henning Stubbe, Sebastian Gallenmüller 2019 Pdf
Manuel Simon Automated Performance Analysis of an FPGA-based P4 Platform IDP Dominik Scholz, Henning Stubbe, Sebastian Gallenmüller 2019 Pdf
Niklas Beck Sensitivity Analysis of Network Calculus and Queuing Network Models BA Max Helm, Benedikt Jaeger, Henning Stubbe 2019 Pdf
tba A Framework for automatic Service Curve Derivation of Network Devices BA, IDP Max Helm, Benedikt Jaeger 2019 Pdf
Stefan Lachnit Mininet Performance Evaluation and Optimization BA Benedikt Jaeger, Max Helm 2019 Pdf
open P4 vs. eBPF: Comparison of Expressiveness, Use Cases and Performance MA, IDP, BA, GR Dominik Scholz, Sebastian Gallenmüller, Henning Stubbe 2019 Pdf