Student Work

We offer students the opportunity to actively participate on interesting and cutting edge research topics and concrete research projects by conducting their thesis in our group.

We offer topics for your Bachelor's Thesis and Master's Thesis to successfully complete your studies with a scientific work. We offer students of the Department of Electrical and Computer Engineering to supervise your Forschungspraxis (research internship /industrial internship) and Ingenieurpraxis directly at our chair. For students with other specializations, such as Informatics, we offer opportunities to supervise your Interdisciplinary Project (IDP) (German: "Interdisziplinäres Projekt (IDP)"). Please contact us directly for more information.

Open Thesis

BAMAIDPFPIPSEMSHK
Title

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Experimental Evaluation of Remote State Estimation in WSN

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Implementation of Multipath-based virtual machine migration

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Working student for Implementation of common Virtual Network Functions

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Measuring the performance overheads in server hypervisors

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Design and Evaluation of a Distributed Optimization framework for SFC Scaling

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Optimal Placement of SDN Controllers and Hypervisors in Virtualized Networks

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Implementation and Evaluation of a Metaheuristic-based Algorithm for Solving Multi-Period Content Placement and Routing

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Implementation and Evaluation of A Nested Approach for Dynamic VM Placement, Routing, and Migration

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An Iterative Algorithm for Resource Management of Flying Airplanes in Space-Air-Ground Integrated Networks

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Working student for innovative Podcasts for BCN lecture

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Tree Splitting with K-Multi Packet Reception

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Working student for managing 5G testbed

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MEC and Network Slicing exploitation in Integrated Satellite-5G Networks Architectures

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Implementation and comparison of two Routing and Spectrum Assignment solutions for flexible optical core networks

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Wireless Reliability Certification Process Simulation

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Performance Evaluation of P4 programmable Devices

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Design and Simulation of a heterogeneous LiFi-WiFi network in NS-3

Ongoing Thesis

Bachelor's Theses

Sensor to Cloud Solution via a Gateway

Scheduling of virtualized network functions

Untersuchung zur rückwärtskompatiblen Datenratensteigerung für proprietäre Brandmeldebustechnik

Accelerating Network Address Translation with NIC Offloading

Master's Theses

Algorithmic Characterization of Unlicensed Spectrum in ISM Band

Modern Random Access Protocol Optimization for Industrial IoT

Multi-channel Tree Resolution Prototype in TDMA for 5G networks

Multi-cell Radio Access Network Slicing

Development and Implementation of a TSCH Scheduler for NCS and WSN

SDN Control Plane Task Offloading using P4

Analysis and optimization of multi-interface mobile networks

Backward Compatible Multi-Path Routing

Practical implementation of a NCS testbed and evaluation of different sampling & flow management policies

Reinforcement Learning Konzept und Proof-of-Concept Implementierung eines Loadbalancers in einem agilen Mesh-Netzwerk

Deep reinforcement learning approach for load balancing in data centers

Research Internship (Forschungspraxis)

System Level Integration of Irregular Repetition Slotted ALOHA for Industrial IoT in New Radio

A Study of Control Plane Traffic in OpenStack Cloud

Implementation and Evualuation of HyperV

OpenFlow Rules Aggregation in the Context of Delay-Constrained Routing

Benchmarking and Evaluation of P4Runtime

Implementing an in-data-plane load-balancing algorithm

Internships

Evaluation of P4 Switches

Boltzmann-Machines: Another Speed-Up Alternative for Your Network Algorithms

Evaluation of a Neural Routing System

A machine Learning Approach to Routing

Survey and Code Analysis of Software Switches

Student Assistant Jobs

Implementation of Energy-Aware Algorithms for Service Function Chain Placement

Student Assistant for the Wireless Sensor Networks Lab WS19/20

Student Assistant for the Wireless Sensor Networks Lab SS19

Working student for the SDN lab

Working Student Position for Network Measurements and Implementations

Working Student Position Machine Learning and Artificial Intelligence