IDP/GR/BT: Data sources for ICN/NDN traffic in IVNs === ## Topic Outline ### Implementation * Prepare realistic ICN/NDN traffic sources, e.g., camera or lidar for experimentation with the EnGINE framework * Creation of a simple NDN data source that can generate periodic, dummy traffic and will be integrated into the EnGINE framework * That source can then be used to generate realistic network traffic originating, e.g., from cameras or lidar. * We have some sensors currently available * The aforementioned application can be modified to convert the video to an NDN format and enable its transmission via our NDN network * Possibly not only video, but also lidar ### Evaluation * Measure video stream parameters and assess them in TSN/IVN context * Investigate the idea of caching and multi-target streams ## Requirements * General computer networking knowledge * Knowledge of C++ and Python is highly recommended * Knowledge of Ansible is a plus, but not a must and can be learned during thesis * Knowledge of NDN/ICN concept is a plus, but not a must and can be learned during thesis ## Further Reading Materials * [EnGINE Methodology and Infrastructure description](https://ieeexplore.ieee.org/document/9910175) * [EnGINE Framework implementation description](https://doi.org/10.1007/s10922-022-09686-0) * [EnGINE Framework open GitHub repository](https://github.com/rezabfil-sec/engine-framework) * [Named-Data Networking](https://named-data.net) ## Contact [Marcin Bosk](https://www.ce.cit.tum.de/cm/research-group/marcin-bosk/)