An SDN/NFV Proof-of-Concept Test-Bed for Machine Learning-based Network Management

Wei Jiang, Mathias Strufe, Michael Gundall, Hans Dieter Schotten

In: Proceedings IEEE ICCC. IEEE International Conference on Computer and Communications (ICCC-2018) December 7-10 Chengdu China IEEE 2018.


Complexity and heterogeneity of the fifth generation (5G) and beyond mobile systems impose a great challenge on current network managing approaches, which are vulnerable, time-consuming and costly. The state-of-the-art research direction in this field is to apply machine learning (ML) techniques to realize intelligent and highly self-organized networking. Unlike the physical layer, theoretical analyses and numerical simulations on the management layer are generally infeasible or not scientifically rigorous enough. Therefore, in this paper, we present a software-defined and virtualized wireless test-bed that is established to evaluate ML-based network management. Based on open-source software and off-the-shelf hardware, this test-bed is easily reproducible, which in turn is hopeful to foster innovative works in this field.


German Research Center for Artificial Intelligence
Deutsches Forschungszentrum für Künstliche Intelligenz