Student Work

Join us in exploring the future of energy-efficient in-building networks! As demand for high-performance wireless connectivity grows, optimizing Access Point (AP) placement is critical to reducing energy consumption and operational costs.

In this work, you will:

• Measure power consumption of WiFi and LiFi networks under different AP placement strategies.
• Use planning tools to simulate and evaluate network layouts.
• Compare energy efficiency and cost per bit for various deployment scenarios.
• Develop recommendations for optimizing AP placement to improve sustainability and reduce costs.

Prerequisites

The goal is to optimize the purification for a given entanglement generation method.

The goal is to see whether the entanglement should be swapped at the request phase or in the ack phase, to increase the resulting fidelity.

Are you ready to dive into cutting-edge technology that merges LiFi and WiFi networks? Imagine your work enabling devices to seamlessly connect across multiple interfaces, pushing the boundaries of what is possible in wireless communication. With multipath solutions like MPTCP and MPQUIC, the potential is immense—but the challenge is real.

We are looking for a motivated student to compare and evaluate various multipath transport protocols on a LiFi-WiFi testbed and assess their suitability for heterogeneous wireless networks by analyzing the advantages and limitations of each protocol.

Related Reading:

1. T. Schmidt, J. Deutschmann, K. -S. Hielscher and R. German, "POSTER: Revisiting Multipath QUIC Experiments and Comparing them with more recent Multipath TCP Implementations," 2021 IEEE International Symposium on Local and Metropolitan Area Networks (LANMAN), Boston, MA, USA, 2021, pp. 1-2, doi: 10.1109/LANMAN52105.2021.9478815.

If you are interested in this work, please send me an email with a short introduction of yourself along with your CV and grade transcript.

Prerequisites

Implemention and Evaluation of Data Streaming Pipelines in a Medical Testbed using MAFs (together with MITI).

Robustness Surfaces are visual tools to understand the resilience of networks in the event of failures. This thesis aims to develop a tool to generate robustness surfaces to quantitatively measure the robustness of networks.

References:

[1] Rueda, Diego F., Eusebi Calle, and Jose L. Marzo. "Robustness comparison of 15 real telecommunication networks: Structural and centrality measurements." Journal of Network and Systems Management 25 (2017): 269-289.

[2]Manzano, Marc, et al. "Robustness surfaces of complex networks." Scientific reports 4.1 (2014): 6133.

Prerequisites

Join us in tackling one of the most pressing challenges in mobile networking—managing the growing demand for data and the need for higher performance in modern applications. As single-network connections struggle to keep up, the 3GPP's Access Traffic Steering, Switching, and Splitting (ATSSS) framework offers a solution, enabling devices to dynamically switch between and simultaneously use multiple network types like 5G, LTE, and Wi-Fi.

In this project, you will:

• Develop a cutting-edge 5G testbed that adheres to 3GPP standards.
• Integrate Multipath TCP to enable seamless communication across multiple network interfaces.
• Contribute to the optimization of mobile traffic management, enhancing both performance and reliability in next-generation networks.

This work is a unique opportunity to get hands-on experience with 5G technology and be at the forefront of mobile networking innovation.

Related Reading:

1. M. Quadrini, D. Verde, M. Luglio, C. Roseti and F. Zampognaro, "Implementation and Testing of MP-TCP ATSSS in a 5G Multi-Access Configuration," 2023 International Symposium on Networks, Computers and Communications (ISNCC), Doha, Qatar, 2023, pp. 1-6, doi: 10.1109/ISNCC58260.2023.10323859.

If you are interested in this work, please send me an email with a short introduction of yourself along with your CV and grade transcript.

Prerequisites

The primary goal of the thesis is to design and implement a FPGA-based system that enables multi-protocol support, automatic detection, and point-to-multipoint communication and contributes to scalable VLC solutions.

Goal: To obtain a rule-based heuristic from a well-performing AI agent for an NP-hard optimization problem. 

AI models, especially deep learning systems, often operate as "black boxes," making complex decisions without revealing how they arrived at a specific conclusion. Explainable AI provides insights into the decision-making process, fostering transparency. As future 5G/6G networks evolve, mobile operators will increasingly rely on AI-driven solutions. For widespread adoption, it's crucial that operators trust these systems, a trust that is far more likely to be built if they can clearly understand how the AI arrives at its decisions.

First, we will focus on extracting the underlying rules that guide AI decision-making. Next, we will aim to develop a rule-based heuristic that can replicate the AI’s performance, offering a simpler yet equally effective solution.

Prerequisites

Primary Goals:

1. Review and understand current CRN implementations in Python
2. Review and summarize candidate optimization methods (Bayesian optimization, random forests, neural networks, ...)
3. Implement and evaluate different proposals from literature using Python
4. Optimize parameters and structure of a CRN for successive interference cancellation
5. Evaluate hyper-parameters, utilize stochastic simulation methods, improving the efficiency of the algorithms

As single-network connections struggle to keep up, the 3GPP's Access Traffic Steering, Switching, and Splitting (ATSSS) framework offers a solution, enabling devices to dynamically switch between and simultaneously use multiple network types like 5G, LTE, and Wi-Fi.

Prerequisites

This master’s thesis addresses the challenge of classifying encrypted traffic in large-scale networks. Traditionally, network operators could monitor and deeply analyze the traffic flowing through their infrastructure to optimize traffic management. However, since the rise of encrypted communications and security concerns, the details accessible by network operators have shrunk to a very high degree. Thus, the current project aims to propose and implement a method for in-network, flow-based encrypted traffic classification.

Alongside the increasing difficulty in classifying and analyzing encrypted traffic comes also the limitations of in-network classification in traditional networks. Traditional network monitoring and analysis methods suffer from little scalability. Therefore, the question addressed in this thesis is whether software-defined networks (SDN) are suitable for in-network traffic classification, relying on SDN-enabled switches distributed across the network operator’s infrastructure. For this classification task, a decision tree classifier implemented using the P4 language and running on the switches is proposed. Finally, the performance and accuracy of implementing such processing will be assessed.

Key points:

• Large-scale traffic classification

• ETC is a hot topic. It provides information to the network operator for optimizing traffic management

• SDN is the new networking paradigm that helps by relying on switches across the network for classification instead of relying on a central network element for it, which could be a bottleneck and could hinder getting real-time analytics.

• Decision Trees as the Machine Learning model used for traffic classification, based on previous work done in the field.

Prerequisites

Optimal Placement of MAF chains considering Priority

The increasing complexity of video analysis tasks has led to the development of sophisticated machine learning applications that rely on multiple interconnected deep-learning models. However, deploying these applications on edge servers with limited resources poses significant challenges in terms of balancing response time, accuracy, and resource utilization.

This research aims to investigate the trade-offs between monolithic and microservice-based architectures for multi-model video analytics applications. We will leverage Apache Ray and Kubernetes to develop a comprehensive benchmarking and monitoring pipeline that systematically analyzes scaling configurations and resource utilization. Our goal is to identify strategies for reducing latency and communication overhead while handling the complexity of multi-model architectures.

Through case studies, we will implement two applications consisting of multiple ML models and explore various deployment configurations, from monolithic to fully microservice-based. We will analyze their performance under different scaling strategies and investigate the impact of model disaggregation on performance metrics during scaling.

The research will focus on addressing key challenges, including:

• Implementing effective monitoring and profiling across distributed services
• Balancing performance and resource utilization across multiple models
• Researching scalability solutions to meet strict latency requirements in edge computing scenarios

Our expected outcomes include a deeper understanding of the trade-offs between monolithic and microservice-based architectures and the development of strategies for optimizing the deployment of multi-model ML applications.

This project aims to identify, analyze, and mitigate antipatterns in AI applications that use microservices-based architectures in distributed systems. The focus will be on Apache Ray within a Kubernetes environment. The goal is to develop strategies to optimize performance and resource efficiency by addressing common antipatterns that can degrade system performance, such as inefficient communication between services, over-provisioning of resources, and poor task distribution.

To achieve this, the project will benchmark AI applications, including video surveillance and action detection systems, to understand how antipatterns emerge and affect key performance metrics like latency, throughput, and resource utilization.

Channel Description for Wireless Access Systems.

The growing interdependence between optical access networks and electrical distribution systems is a key factor in maintaining the reliability of essential services in urban environments. As cities increasingly rely on both power and digital connectivity, the resilience of these interconnected infrastructures has become more critical than ever. This thesis explores the integration of various protection schemes within Passive Optical Networks (PON) and assesses their dependability on electrical distribution networks under multiple failure scenarios.

The protection schemes examined include the Unprotected scheme, as well as more robust configurations such as Type A (Feeder Fiber Protection), Type B (Dual Parented), Type C, and Type C2, which offer varying levels of reliability. These protection strategies aim to mitigate the risks posed by network failures, ensuring uninterrupted service in urban areas where dependability is essential.

A primary goal of this thesis is to develop a generic tool that can assess the dependability of optical and electrical networks, particularly within the context of FttX (Fiber to the X) architectures. While the focus will primarily be on FttC (Fiber to the Cabinet), the tool might also explore potential applications in FttB (Fiber to the Building) and FttH (Fiber to the Home) scenarios. By using OpenStreetMap (OSM) data to model real-world urban layouts, the tool will integrate these protection schemes into a PON planning system to design both optical and electrical network topologies.

Additionally, the tool will feature a failure analysis component that simulates different failure types – such as node, edge, and disaster failures – to generate robustness metrics. These analyses will be complemented by visualizations such as robustness surfaces and statistical breakdowns, offering insights into the resilience of urban infrastructures. Through this approach, the thesis aims to enhance the overall understanding of how optical and electrical networks respond to stress, with a focus on ensuring robustness and reliability in densely populated urban settings.

This thesis aims to achieve its objectives through a combination of Python scripting, data analysis libraries, and geospatial data sources. As a geospatial data source, OSM is planned to be used, and for processing and visualizing the networks Python will be used. Key Python libraries include Folium, which is employed to plot the networks interactively on maps, and NetworkX, used for creating and analyzing the structure of complex network topologies. Pandas can be used in managing and analyzing the large datasets generated from OSM and network simulations. Visualization tools such as Matplotlib, Seaborn and Folium will be utilized to create both static and interactive visual representations of the data, including network layouts and failure impacts. Together, these tools will enable a robust analysis of network dependability across optical and electrical infrastructures.

Prerequisites

Join us in tackling one of the most pressing challenges in mobile networking—managing the growing demand for data and the need for higher performance in modern applications. As single-network connections struggle to keep up, the 3GPP's Access Traffic Steering, Switching, and Splitting (ATSSS) framework offers a solution, enabling devices to dynamically switch between and simultaneously use multiple network types like 5G, LTE, and Wi-Fi.

In this project, you will:

• Develop a cutting-edge 5G testbed that adheres to 3GPP standards.
• Integrate Multipath TCP to enable seamless communication across multiple network interfaces.
• Contribute to the optimization of mobile traffic management, enhancing both performance and reliability in next-generation networks.

This work is a unique opportunity to get hands-on experience with 5G technology and be at the forefront of mobile networking innovation.

Related Reading:

1. M. Quadrini, D. Verde, M. Luglio, C. Roseti and F. Zampognaro, "Implementation and Testing of MP-TCP ATSSS in a 5G Multi-Access Configuration," 2023 International Symposium on Networks, Computers and Communications (ISNCC), Doha, Qatar, 2023, pp. 1-6, doi: 10.1109/ISNCC58260.2023.10323859.

If you are interested in this work, please send me an email with a short introduction of yourself along with your CV and grade transcript.

Prerequisites

Are you ready to dive into cutting-edge technology that merges LiFi and WiFi networks? Imagine your work enabling devices to seamlessly connect across multiple interfaces, pushing the boundaries of what's possible in wireless communication. With multipath solutions like MPTCP and MPQUIC, the potential is immense—but the challenge is real.

We are looking for a motivated student to design and implement a state-of-the-art wireless-channel-aware packet scheduler. You'll tackle the complex task of scheduling data packets across multiple network paths, each with unique characteristics like delay and packet loss.

Related Reading:

1. W. Yang, L. Cai, S. Shu, J. Pan and A. Sepahi, "MAMS: Mobility-Aware Multipath Scheduler for MPQUIC," in IEEE/ACM Transactions on Networking, vol. 32, no. 4, pp. 3237-3252, Aug. 2024, doi: 10.1109/TNET.2024.3382269.

If you are interested in this work, please send me an email with a short introduction of yourself along with your CV and grade transcript.

Prerequisites

In future communication systems such as 6G, in-network computing will play a crucial role. In particular, processing units within the network enable to run applications such as digital twins close to the end user, leading to lower latencies and overall better performance. For this, the execution location of these applications should be changed dynamically according to the available networking resources.

 In this thesis, the task is therefore to develop and evaluate an approach to optimize the migration of medical applications, i.e., modular application functions (MAFs), when executed in the network. The challenge of this migration lies in the connection quality during the migration and the migration of stateful applications, i.e., using memory.

 The result will be an evaluated placement approach for applications in the medical environment considering the availability.

Prerequisites

The widespread deployment of Fiber-to-the-Home (FttH) in various markets has given consumers access to high-speed data connections over the extensive optical fiber-based core networks. End users usually access these networks with wireless devices using the 802.11 standard. However, as the next generation of IoT devices with VR and AI applications enter the market, the demand for improved bandwidth and latency has increased drastically. This has led to the development of Fiber-to-the-Room (FttR) networks, which seek to extend the fiber connections closer to the terminal devices by eliminating the bottleneck caused by traditional ethernet and wireless access. Current implementations utilize a cascaded XGPON optical distribution network (ODN) in convergence with WiFi 6. The ONU at the user’s premises is replaced with a Main FttR Unit (MFU), which acts as the OLT for the Sub FttR Units (SFU) in each room using point-to-multipoint architecture. The SFUs convert the optical signals to baseband and retransmit the data as WiFi frames.

These solutions keep both MAC and PHY layers between the optical transport and WiFi completely separated without using any synergies. This introduces various limitations to the FttR setup, such as degraded data rates, jitter / latency, and high power consumption. To solve these problems, a centralized wireless - optical access network (C-WAN) has been conceptualized, where the MFU becomes a central controller to enable seamless roaming, with deterministic low latency transmission and gigabit coverage for the entire room. Within the scope of this solution, a cross-domain MAC layer between optical and WiFi has been proposed to implement dynamic resource management and scheduling. Such a centralized and converged MAC protocol must reduce overhead and optimize the framing of both physical layers to minimize the processing delay at the SFUs. This thesis aims to design and evaluate such a minimal optical access protocol with a centralized controller and test its performance in an FttR setup. The ns-3 network simulator is used within the context of this thesis to implement, simulate, and analyze the designed protocol with C++. Extensive modules that simulate both XGPON and WiFi 6 are already implemented in ns-3 and can be modified as required.

In this topic an analysis of Broadcast messages in 4G and 5G should be done. There exist several different kind of these messages with different functions and level of information content. The analysis should consider privacy and security aspects. After the theoretical review and analysis the practical part should focus on one aspect of the findings. An implementation of one security and privacy aspect should be done as a proof-of-concept with Open Source hard- and software.

The following things are requested to be designed, implemented, and evaluated (most likely via proof-of-concept) in this thesis:
• Security and privacy analysis of Broadcast Messages
• Implementation of an attack
• Practical evaluation with testing of commercial smartphones

We will offer you:
• Initial literature
- https://dl.acm.org/doi/10.1145/3307334.3326082
• Smart working environment
• Deep contact to supervisors and a lot of discussions and knowledge exchange

A detailed description of the topics will be formulated with you in initial meetings. For sure, the report needs to be written based on the requirements of the universities, as well as a detailed documentation and handing over the complete project with all sources. Depending on the chosen thesis type the content will be adapted in its complexity.

All applications must be submitted through our application website INTERAMT:

https://interamt.de/koop/app/stelle?0&id=1242375

Carefully note the information provided on the site to avoid any issues with your application.

Please include
• a short CV
• current overview of your grades
• the keyword "T3-MK-BROADCAST" as comment
in your application.

For any questions or further details regarding this thesis and the application process, please don't hesitate to contact:
• TUM contact: nicolai.kroeger@tum.de, serkut.ayvasik@tum.de
• Forschungreferat T3 (ZITiS), Email: t3@zitis.bund.de

Prerequisites

This work aims to find the best links that, when added to the network, improve the network sovereignty.

Prerequisites

In future communication systems such as 6G, in-network computing will play a crucial role. In particular, processing units within the network enable to run applications such as digital twins close to the end user, leading to lower latencies and overall better performance.

 In this thesis, the task is to develop and evaluate an approach to optimize the availability  of medical applications, i.e., modular application functions (MAFs), when executed in the network. For that, suitable real use cases are identified together with our partners at MITI (Hospital "Rechts der Isar"). The optimizing approach then leads to a specified distribution of the processing and networking resources, satisfying the minimum needs of critical applications while considering the needed availability.

 The result will be an evaluated placement approach for applications in the medical environment considering the availability.

Prerequisites

In future communication systems such as 6G, in-network computing will play a crucial role. In particular, processing units within the network enable to run applications such as digital twins close to the end user, leading to lower latencies and overall better performance.

 In this thesis, the task is to develop and evaluate an approach to minimize the power consumptions  of medical applications, i.e., modular application functions (MAFs), when executed in the network. For that, suitable real use cases are identified together with our partners at MITI (Hospital "Rechts der Isar"). The optimizing approach then leads to a specified distribution of the processing and networking resources, satisfying the minimum needs of critical applications while considering the power consumption.

 The result will be an evaluated power minimizing approach for applications in the medical environment.

Prerequisites

In future communication systems such as 6G, in-network computing will play a crucial role. In particular, processing units within the network enable to run applications such as digital twins close to the end user, leading to lower latencies and overall better performance.

 In this thesis, the task is to place medical applications, i.e., modular application functions (MAFs), in the networking considering various parameters similar to [1]. For that, suitable real use cases are identified together with our partners at MITI (Hospital "Rechts der Isar"). The optimizing approach then leads to a specified distribution of the processing and networking resources, considering various important parameters.

 The result will be an evaluated placement approach for applications in the medical environment.

[1] A. Hentati, A. Ebrahimzadeh, R. H. Glitho, F. Belqasmi and R. Mizouni, "Remote Robotic Surgery: Joint Placement and Scheduling of VNF-FGs," 2022 18th International Conference on Network and Service Management (CNSM), Thessaloniki, Greece, 2022, pp. 205-211, doi: 10.23919/CNSM55787.2022.9964591.

Prerequisites

5G is the newest generation of mobile networks, allowing for higher data rates, lower latency and many new features like network slicing. Its central element is the 5G Core, which is a network of specialised Network Functions (NFs). One of these NFs is responsible for roaming connections. Roaming allows subscribers to connect to the internet via other network operators’ networks if they have a roaming agreement. Between two Public Land Mobile Networks (PLMNs), there are two standardised Roaming modes: Local Break Out and Home Routed Roaming. For Local Break Out Roaming, only the home network’s control plane is accessed from the visited network, while the user data is directly transmitted to the Data Network (DN). For Home Routed Roaming, the user data is routed through the home network to the DN. This thesis aims to implement both Roaming versions in an open-source core network and compare them regarding chosen KPIs, e.g., latency or throughput. Open5GS would be the primary choice for the open-source core network, as it already supports Local Break Out Roaming. Home Routed Roaming is not yet supported.

A major part of 5G roaming is the Security Edge Protection Proxy (SEPP), a 5G NF designed to establish and maintain a secure control plane connection between two PLMNs. Implementing it, or extending the existing implementation of Open5GS, will be an important part of this work. The SEPP is connected to other NFs in the same PLMN via Service Based Interfaces (SBIs) and to other PLMN’s SEPPs via the N32 interface.

The biggest difference between the two roaming scenarios lies in the data plane routing, so implementing the connection between two User Plane Functions (UPFs), the N9 interface, is necessary to connect two PLMNs. The newly introduced Inter PLMN User Plane Security (IPUPS) used for additional security on this connection is initially considered out-of-scope for this work but may be added later.

A security analysis regarding control and user plane for both roaming modes finishes this work’s contributions. Potential focal points are the control capabilities of the home PLMN operator in Local Break Out Roaming.

Prerequisites

Problem: BGP is performance-agnostic

Solution: incorporate a delay-related metric into the best-path selection process.

Approach: Estimate the round-trip prop_delay to destinations (/24s) within the routing table of the IXP

Goal: Evaluate if it is possible to outperform BGP’s route selection criterion, in terms of latency, with a measurement-based approach.

The master thesis aims to develop a connected sensor fusion system focusing on its application in Urban Air Mobility localization. By gathering data from multiple sensors, the air vehicles (AVs) will be able to better estimate the airspace view and improve their route planning.  The performance of IoT protocols within the context of a 6G system will be assessed. The study also seeks to evaluate the impact of network performance factors, such as delay and packet loss, on the accuracy of the fusion data. Additionally, the thesis will investigate the impact of a semantic-aware transport layer on the performance of the fusion system. Ultimately, the research not only contributes to the advancement of UAM technology but also aligns with the emerging 6G paradigm, offering a more connected and efficient solution for tactical deconfliction in airspace navigation, making it safer and more reliable.

The thesis studies a Markov model of two correlated sources (X and Y) transmitting the data over a wireless channel for remote estimation. The objective of the thesis is to develop a strong theoretical insight for modelling an estimator to optimize the errors and age of information in a wireless communication system. We aim at studying various estimation strategies to do so, and demonstrate the optimal method for the given conditions (such as correlation between the sources, and Markov model parameters). The implementation is carried out by simulating the abovementioned theoretical concepts in MATLAB under different conditions.

The analysis of a dual data-gathering strategy for Internet-of-Things (IoT) devices in status update systems offers valuable insights into improving the efficiency and reliability of data collection in IoT environments. This thesis focuses on investigating the dual data gathering strategy, aiming to optimize the performance of status update systems in IoT deployments. The dual data-gathering strategy takes advantage of both local and remote processing capabilities. Using different source servers, this strategy aims to reduce energy consumption and network congestion in status update systems. The anticipated outcomes of this research include a comprehensive understanding of the dual data gathering strategy, mathematical models to analyze its performance, and insights into its practical implementation. These outcomes will not only advance the theoretical understanding of status update systems in IoT but also have practical implications for the design and deployment of IoT networks and applications.

Providing Quality of Service (QoS) to emerging time-sensitive applications such as factory automation, telesurgery, and VR/AR applications is a challenging task [1]. Time Sensitive Networks (TSN) [2] and Deterministic Networks [3] were developed for such applications to guarantee ultra low latency, bounded latency and jitter, and zero congestion loss. The objective of this work is to develop a methodology to guarantee bounded End-to-End (E2E) latency and jitter in large-scale networks.

Prerequisites

This work will investigate how deep reinforcement learning can be leveraged to automate and optimize task offloading strategies while incorporating explainability techniques to make AI-driven decisions more transparent and interpretable. The goal is to develop a system that not only improves efficiency but also provides insights into why certain decisions are made, increasing trust and usability in real-world deployments

Prerequisites

Wi-Fi 7 introduces Multi-Link Operation (MLO) – a technology that enables devices to transmit and receive data across multiple frequency bands simultaneously. This innovation optimizes network performance and reliability especially in high-density environments.

In this thesis, you'll evaluate resource allocation strategies for MLO using the ns-3 network simulator. Join this exciting research and help shape the next generation of wireless communication!

Related Reading:

1. M. Carrascosa-Zamacois, G. Geraci, E. Knightly and B. Bellalta, "Wi-Fi Multi-Link Operation: An Experimental Study of Latency and Throughput," in IEEE/ACM Transactions on Networking, vol. 32, no. 1, pp. 308-322, Feb. 2024, doi: 10.1109/TNET.2023.3283154.
2. L. Zhang, H. Yin, S. Roy, L. Cao, X. Gao and V. Sathya, "IEEE 802.11be Network Throughput Optimization With Multi-Link Operation and AP Controller," in IEEE Internet of Things Journal, doi: 10.1109/JIOT.2024.3386653.

If you are interested in this work, please send me an email with a short introduction of yourself along with your CV and grade transcript.

Prerequisites

Deterministic, low-latency and reliable communication of time-sensitive data is a critical challenge in industrial and automotive networks. IEEE introduced the Ethernet standards Time-Sensitive Networking (TSN) to address these requirements. Besides traffic prioritization and scheduling, TSN supports the Frame Replication and Elimination for Reliability (FRER) mechanism to transmit packets via redundant paths in a parallel way. Industry 4.0 has intensified the need for mobility, such as using Automated Guided Vehicles (AGVs). To meet these demands, 5G must be integrated into the TSN system. To support end-to-end redundancy compensating varying channel qualities and packet loss, FRER shall be integrated into the TSN+5G network.

Goal of this Research Internship (Forschungspraxis) is the implementation of FRER in the OMNeT++ simulator using the frameworks inet and simu5g. Based on the implementation, different scenarios shall be simulated and analyzed considering varying topologies and traffic scenarios.

Prerequisites

The introduction of 5G technology is transforming the telecommunications industry, offering enhanced connectivity and supporting advanced use cases such as IoT, ultra-reliable low-latency communications, and enhanced mobile broadband. 

A key challenge in this ecosystem is enabling seamless 5G roaming between different mobile network operators (MNOs) across borders, which requires reliable interconnection via IP eXchange (IPX) networks.

This research internship aims to explore the feasibility of using Mininet, a network emulation tool, in conjunction with Open5GS, an open-source 5G core network implementation, to simulate basic IPX functionalities for supporting 5G Standalone (SA) roaming use cases. 

The focus will be on setting up the system, adding support for needed protocols and integrating the Mininet-IPX-setup into the current LKN 5G Roaming Testbed.

Prerequisites

Containerizing the ROS2 components according to the MAF concept.

Serverless computing is a cloud computing paradigm that separates infrastructure management from software development and deployment. It offers advantages such as low development overhead, fine-grained unmanaged autoscaling, and reduced customer billing. From the cloud provider's perspective, serverless reduces operational costs through multi-tenant resource multiplexing and infrastructure heterogeneity.

    However, the serverless paradigm also comes with its challenges. First, a systematic methodology is needed to assess the performance of heterogeneous open-source serverless solutions. To our knowledge, existing surveys need a thorough comparison between these frameworks. Second, there are inherent challenges associated with the serverless architecture, specifically due to its short-lived and stateless nature.

Clustering is already used in our cities to distribute splitters for managing network operations. However, the current distribution does not effectively reduce the costs caused by huge urban area with long fiber lengths. To solve this, we can use k-means clustering to group the splitters and optimize how fibers are laid out in the city.

With k-means clustering, we group users (ONUs) in an area to create a virtual center. This center is chosen so that the total distance to all users in the area is minimized. We then find a nearby point where a splitter can be placed, ensuring the distance from the splitter to the users is as short as possible.

Next, we cluster the remote nodes (RNs) where splitters are located. By grouping nearby splitters, we can combine their connections into one line to the central office (OLT). This line will be organized by a new splitter near to the center of the old splitter's cluster center. This helps reduce the total fiber length needed and lowers deployment costs.

Prerequisites

...

The Internship aims to analyze Open Source Optical Network Data for performance prediction of Optical Networks and develop data-driven methods for quality of transmission estimation.

Deterministic, low-latency communication for time-sensitive data is a critical challenge in industrial and automotive networks. IEEE introduced the Ethernet standards Time-Sensitive Networking (TSN) to address these requirements. Using traffic prioritization and scheduling, TSN enables deterministic, reliable, and low-latency communication. However, industry 4.0 has intensified the need for mobility, such as using Automated Guided Vehicles (AGVs). To meet these demands, 5G must be integrated into TSN systems.

Your role will involve enhancing and further developing a TSN-5G testbed. A baseline testbed integrating 5G into TSN is already in place. The next phase of development focuses on integrating reliability mechanisms. Your specific tasks will include:

• Measuring and analyzing end-to-end delays.
• Setting up and integrating additional devices, such as UEs, into the testbed.
• Integrating a network controller into the system.
• Adapting the controller to support additional mechanisms.

What you’ll gain:

• Experience with networking hardware.
• Expertise in hardware measurements.
• Practical experience in system implementation.

Depending on your availability, your working hours per week can be between 10 and 20. If this opportunity interests you, please send us a brief introduction about yourself along with your CV and transcript of records. We look forward to meeting you!

Prerequisites

5G is the newest generation of mobile networks allowing for higher data-rates, lower latency and many new features like network slicing. Its central element is the 5G Core, which is a network of specialised Network Functions (NFs). Roaming allows subscribers to connect to the internet via other network operator’s networks if they have a roaming agreement. We are looking for a student to help implement and maintain a 5G Roaming testbed. At first, that is planned as an open source testbed leveraging Open5GS. Later, the plan is to connect this open source testbed to the LKN campus network.

This working student position may run parallel to Master Theses with more focused implementation and evaluation works. The working student is welcome to follow up on this work with his/ her own research internship or Master’s thesis.

Objectives

The primary objective of this work is to help implement and maintain a 5G Roaming testbed. This testbed shall then be used for investigation of security mechansims and performance measurements. Those are not the main job of the student, but the student is supposed to help.

1. Work into 5G Roaming

2. Implement missing Roaming functionalities into Open5GS

3. Maintain Roaming Testbed

4. Connect open source 5G Roaming testbed with Campus Network (once possible)

5. Aid in security investigations

6. Aid in performance measurements

7. Potentially add other NFs later

Prerequisites

The Wireless Sensor Networks lab offers the opportunity to develop software solutions for the wireless sensor networking system, targeting innovative applications. For the next semester, a position is available to assist the participants in learning the programming environment and during the project development phase. The lab is planned to be held on-site every Tuesday 15:00 to 17:00.

Prerequisites

Future medical applications put stringent requirements on the underlying communication networks in terms of highest availability, maximal throughput, minimal latency, etc. Thus, in the context of the 6G-life project, new networking concepts and solutions are being developed.

For the research of using 6G for medical applications, the communication and the medical side have joined forces: While researchers from the MITI group (Minimally invasive Interdisciplinary Therapeutical Intervention), located at the hospital "Rechts der Isar", focus on the requirements of the medical applications and collecting needed parameters of patients, it is the task of the researchers at LKN to optimize the network in order to satisfy the applications' demands. The goal of this joint research work is to have working testbeds for two medical testbeds located in the hospital to demonstrate the impact and benefits of future 6G networks and concepts for medical applications.

Your task during this work is to implement the communcation network for those testbeds. Based on an existing open-access 5G network implementation, you will implement changes according to the progress of the current research. The results of your work, working 6G medical testbeds, will enable researchers to validate their approaches with real-world measurements and allow to demonstrate future 6G concepts to research, industry and politics.

In this project, you will gain a deep insight into how communication networks, especially the Radio Access Network (RAN), work and how different aspects are implemented. Additionally, you will understand the current limitations and weaknesses as well as concepts for improvement. Also, you will get some insights into medical topics if interested. As in such a broad topic there are many open research questions, you additionally have the possibility to also write your thesis or complete an internship.

Prerequisites