Model-based Analysis of Next-Generation Networks
|Scientists:||Benedikt Jaeger, M. Sc., Sebastian Gallenmüller, Max Helm, M. Sc., Dominik Scholz, M.Sc., Henning Stubbe, Prof. Dr.-Ing. Georg Carle|
|Duration:||01.07.2019 – 30.09.2022|
|Funding:||Deutsche Forschungsgemeinschaft (DFG)|
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
|Alexander Frank||Evaluation and Analysis of a Hardware Programmable High-Performance Switch||MA||Dominik Scholz, Sebastian Gallenmüller, Henning Stubbe||2019|
|Henning Stubbe||Performance Analysis of P4 on NetFPGA||MA||Dominik Scholz, Sebastian Gallenmüller, Fabien Geyer||2018|
|Oliver Schmidt||A Framework for In-band Network Telemetry using P4||GR||Dominik Scholz, Sebastian Gallenmüller, Fabien Geyer||2018|
|Henning Stubbe||Implementing a P4 Benchmarking Suite for libmoon||IDP||Sebastian Gallenmüller, Dominik Scholz, Fabien Geyer||2017|
|Oliver Schmidt||P4: A Programming Language for Packet Processing||BA||Sebastian Gallenmüller, Dominik Scholz||2016|
Open and running student theses
|Marcel Mussner||Comparing Network Calculus Guarantees with Latency Measurements in Emulated Networks||BA||Max Helm, Dominik Scholz, Benedikt Jaeger, Henning Stubbe||2019|
|Ivan Kendzor||Modeling Scheduling Algorithms in Network Calculus||BA||Max Helm, Henning Stubbe, Dominik Scholz, Fabien Geyer||2019|
|Stefan Stark||A Framework for Analysis of Network Performance Metrics||MA||Dominik Scholz, Sebastian Gallenmüller||2019|
|Felix Hartmond||Network Device Benchmarking with an 100Gb/s SDN Router||MA||Dominik Scholz, Sebastian Gallenmüller, Henning Stubbe||2019|
|Maximilian Endraß||Performance Evaluation of Software Dataplanes||MA||Dominik Scholz, Henning Stubbe, Sebastian Gallenmüller||2019|
|Manuel Simon||Automated Performance Analysis of an FPGA-based P4 Platform||IDP||Dominik Scholz, Henning Stubbe, Sebastian Gallenmüller||2019|
|tba||Sensitivity Analysis of Network Calculus and Queuing Network Models||BA, IDP||Max Helm, Benedikt Jaeger, Henning Stubbe||2019|
|tba||A Framework for automatic Service Curve Derivation of Network Devices||BA, IDP||Max Helm, Benedikt Jaeger||2019|
|tba||Mininet Performance Evaluation and Optimization||BA, MA, IDP, GR||Benedikt Jaeger, Max Helm||2019|
|Burak Atalay||A Framework for Automated Analysis of P4Runtime||MA||Dominik Scholz, Fabien Geyer, Sebastian Gallenmüller||2018|