Student Assistant for Programmable Communication Networks Lab Summer Semester 2025
Beschreibung
PCN lab offers the opportunity to familiarize with Openflow and P4 for computer networks. For the next semester, a position is available to assist the participants during labs and the project phase. The lab is planned to be held on-site every Wednesday from 13:00 to 17:00.
Voraussetzungen
- Knowledge of communication networks.
- Solid programming skills: Python.
- Linux knowledge.
Kontakt
kaan.aykurt@tum.de
nicolai.kroeger@tum.de
Betreuer:
Automated Configuration of Complex Networks Using AI-Driven Intent-Based Networking
Networks, Artificial Intelligence, Intent-Based Networking, Large Language Models
Beschreibung
In today’s business landscape, the demand for highly available, secure, and scalable networks is continuously increasing, particularly for large enterprises.
Conventional network management faces challenges such as complexity, with manual configurations being error-prone and time-consuming. It also struggles with scalability issues due to slow adaptation to changing needs and limited automation, which requires deep expertise. Modern solutions like SDN, NFV, and AI-driven automation address these problems by enabling dynamic, scalable, and policy-driven network management.
The traditional network management approach relies on manual implementation, requiring expertise in routing, Quality of Service (QoS), and encryption mechanisms. This results in high operational costs and makes the network prone to misconfigurations. Intent-Based Network Configuration Management is a modern approach to managing and automating networks, where the operator defines "what they want the network to do" (the intent) rather than specifying "how to configure the network" (manual steps). The system interprets these high-level intents and automates the necessary configurations and adjustments to achieve the desired outcome.
Voraussetzungen
• Knowledge in Network Automation and Network Orchestration
• AI and Machine Learning Fundamentals
• Proficiency in programming and scripting, with a strong focus on Python and knowledge in libraries such as TensorFlow and PyTorch
• High level of self-motivation, independence, and problem-solving capability
Kontakt
kaan.aykurt@tum.de
philip.ulrich@telekom.de
klaus.scheepers@telekom.de