Studentische Arbeiten

Wir bieten Studierenden die Gelegenheit zur aktiven Mitarbeit an spannenden und hochaktuellen Forschungsthemen und Forschungsprojekten im Rahmen ihrer Prüfungsleistungen.

Bei uns können Sie Ihre Bachelor- (BA) und Masterarbeit (MA) sowohl direkt am Lehrstuhl als auch in der Industrie durchführen. Studierende der Elektrotechnik und Informationstechnik können bei uns ihre Ingenieurpraxis (IP) und ihre Forschungspraxis (FP) direkt am Lehrstuhl durchführen. Für Studierende aus anderen Studiengängen, wie z.B. der Informatik, bieten wir "Interdisziplinäre Projekte (IDPs)" an. Bitte kontaktieren Sie uns hierzu direkt.

Auf dieser Seite finden Sie auch offene Stellen für wissenschaftliche Hilfskräfte (Werkstudenten), gekennzeichnet mit SHK.

Zu einem Thema sind verschiedene Arten von Arbeiten möglich. Das Thema wird dann entsprechend der Zielsetzung im Schwierigkeitsgrad und Aufwand z.B. BA oder MA angepasst.

Bitte beachten: Auf dieser Seite listen wir auch die bereits vergebenen Arbeiten "Laufende Arbeiten", damit Sie einen Eindruck bekommen, welche Themengebiete bearbeitet werden. Wenn Ihnen ein Thema bei den Laufenden Arbeiten gefällt, dann kontakrieren Sie die Betreuerin/den Betreuer und fragen, ob es eine Folgearbeit zu einem ähnlichen Thema gibt. Oft ist dies der Fall.

Offene Arbeiten

Investigating the Detectability of Hidden Communication in 5G Core Networks

Beschreibung

Mobile networks are now ubiquitous and part of our everyday lives. Due to their important role in public security and safety, they are classified as critical infrastructure and need to be protected accordingly. At the same time, 5G shifted from a closed system to a set of microservices designed to be deployed in dynamic environments such as (public) clouds. This large number of involved systems and components increases the risk of infiltration by bad actors through security flaws and supply chain issues. To understand how a compromised core network can be exploited, we described a steganography based system able to execute various attacks and implemented a proof-of-concept. This framework should now be extended and evaluated against state-of-the-art detection mechanisms.

Objectives:

• Implement the framework in an open source 5G core network (such as Open5GS, Free5GC and OpenAir-Interface).

• Perform tests on the feasibility of various attacks in this framework.

• Evaluate 5G intrusion detection and prevention approaches described in the literature.

Voraussetzungen

• Basic understanding of cellular radio communication (such as LTE, 5G NR) specifically their architecture and protocols.

• Basic knowledge of network security.

• Solid knowledge of C/C++ and/or Golang.

 

Please include:

• a short CV

• a current overview of your grades

in your application.

For any questions or further details regarding this thesis and the application process, please don’t hesitate to contact:

• Julian Sturm (TUM), Email: julian.sturm@tum.de

Kontakt

Julian Sturm (TUM), Email: julian.sturm@tum.de

Betreuer:

Oliver Zeidler

Finding and Identifying Publicly Accessible 5G Core Networks

Stichworte:
5G, 5G Core, Security, IP

Beschreibung

Mobile networks are now ubiquitous and part of our everyday lives. Due to their important role in public security and safety, they are classified as critical infrastructure and need to be protected accordingly. At the same time, 5G shifted from a closed system to a set of microservices designed to be deployed in dynamic environments such as (public) clouds. Previous research shows, that often critical systems are identifiable from the internet with little to no protection (Bodenheim et al. 2014). For 5G however, such data is lacking.

Objectives:

• Develop methods to identify components of open source 5G core networks (such as Open5GS, Free5GC and OpenAirInterface), as well as commercial networks based on their network fingerprint.

• Perform internet scanning to search for publicly accessible networks.

• Evaluate the prevalence of deployed security mechanisms (if scans are successful).

Voraussetzungen

• Basic understanding of cellular radio communication (such as LTE, 5G NR) specifically their architecture and protocols.

• Solid understanding of IP networks, specifically their architecture and protocols.

• Solid knowledge of Python or another suitable programming language.

 

Please include:

• a short CV

• a current overview of your grades

in your application.

For any questions or further details regarding this thesis and the application process, please don’t hesitate to contact:

• Julian Sturm (TUM), Email: julian.sturm@tum.de

Kontakt

Julian Sturm (TUM), Email: julian.sturm@tum.de

Betreuer:

Oliver Zeidler

Harnessing Large Language Models for Intelligent Wireless Networking

Beschreibung

Explore the exciting world of Large Language Models (LLMs) with us!
As LLMs (like GPT-4) transform industries worldwide, this is your chance to be part of this transformative journey in wireless networking.

In this project, you will:

  • Re-implement and analyze cutting-edge LLMs, evaluating their strengths, limitations, and specific applications in wireless networking.
  • Identify and tailor these models to a unique use case in wireless networking, applying state-of-the-art techniques to solve real-world challenges.

Related Reading:

  1. Shao, Jiawei, Jingwen Tong, Qiong Wu, Wei Guo, Zijian Li, Zehong Lin, and Jun Zhang. "WirelessLLM: Empowering Large Language Models Towards Wireless Intelligence." arXiv preprint arXiv:2405.17053 (2024).

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.

 

Voraussetzungen

  • Strong Python programming skills
  • Strong foundation in wireless networking concepts
  • Prior experience with machine learning frameworks

Betreuer:

Development of a 5G Multipath TCP Testbed for Multi-Access Network Optimization

Beschreibung

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.

 

Voraussetzungen

  • Experience with programming in C/C++
  • Strong foundation in wireless networking concepts
  • Motivation to learn 5G concepts
  • Availability to work in-presence

Betreuer:

Design and Implementation of an Intelligent Multipath Packet Scheduler

Beschreibung

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.

Voraussetzungen

  • Experience with Linux networking
  • Strong foundation in wireless networking concepts
  • Availability to work in-presence

Betreuer:

Mobile Communication RRC Message Security Analysis

Stichworte:
5G, SDR, Security, RAN

Beschreibung

In this topic an analysis of RRC 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 focus should lay on messages related to the connection release. The analysis should consider privacy and security aspects. After the theoretical review and analysis the practical part should focus on an attack. 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 availability analysis of specific RRC messages
• Implementation of an attack
• Practical evaluation with testing of commercial smartphones

We will offer you:
• Initial literature
  - https://doi.org/10.14722/NDSS.2016.23236
• 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?id=1103974

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-RRC" 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

Voraussetzungen

Knowledge in the following fields is required:
• C/C++
Knowledge in the following fields would be an advantage:
• Mobile Communication 4G, 5G

Kontakt

• TUM contact: nicolai.kroeger@tum.de, serkut.ayvasik@tum.de
• Forschungreferat T3 (ZITiS), Email: t3@zitis.bund.de

Betreuer:

Serkut Ayvasik, Nicolai Kröger - (Zentrale Stelle für Informationstechnik im Sicherheitsbereich (ZITiS))

Mobile Communication Broadcast Message Security Analysis

Stichworte:
5G, SDR, Security, RAN

Beschreibung

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?id=1103974

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

Voraussetzungen

Knowledge in the following fields is required:
• C/C++
Knowledge in the following fields would be an advantage:
• Mobile Communication 4G, 5G

Kontakt

• TUM contact: nicolai.kroeger@tum.de, serkut.ayvasik@tum.de
• Forschungreferat T3 (ZITiS), Email: t3@zitis.bund.de

Betreuer:

Serkut Ayvasik, Nicolai Kröger - (Zentrale Stelle für Informationstechnik im Sicherheitsbereich (ZITiS))

Latency and Reliability Guarantees in Multi-domain Networks

Stichworte:
Multi-domain networks

Beschreibung

One of the aspects not covered by 5G networks are multi-domain networks, comprising one or more campus networks. There are private networks, including the Radio Access Network and Core Network, not owned by the cellular operators like within a university, hospital, etc. There will be scenarios in which the transmitter is within a different campus network from the receiver, and the data would have to traverse networks operated by different entities.

Given the different operators managing the “transmitter” and “receiver” networks, providing any end-to-end performance guarantees in terms of latency and reliability can pose significant challenges in multi-domain networks. For example, if there is a maximum latency that a packet can tolerate in the communication cycle between the transmitter and receiver, the former experiencing given channel conditions would require a given amount of RAN resources to meet that latency. The receiver, on the other end of the communication path, will most probably experience different channel conditions. Therefore, it will require a different amount of resources to satisfy the end-to-end latency requirement. Finding an optimal resource allocation approach across different networks that would lead to latency and reliability guarantees in a multi-domain network will be the topic of this thesis.     

Voraussetzungen

The approach used to solve these problems will rely on queueing theory. A good knowledge of any programming language is required.

Betreuer:

Fidan Mehmeti

Decentralized Federated Learning on Constrained IoT Devices

Beschreibung

The Internet of Things (IoT) is an increasingly prominent aspect of our daily lives, with connected devices offering unprecedented convenience and efficiency. As we move towards a more interconnected world, ensuring the privacy and security of data generated by these devices is paramount. That is where decentralized federated learning comes in.

Federated Learning (FL) is a machine-learning paradigm that enables multiple parties to collaboratively train a model without sharing their data directly. This thesis focuses on taking FL one step further by removing the need for a central server, allowing IoT devices to directly collaborate in a peer-to-peer manner.

In this project, you will explore and develop decentralized federated learning frameworks specifically tailored for constrained IoT devices with limited computational power, memory, and energy resources. The aim is to design and implement efficient algorithms that can harness the collective power of these devices while ensuring data privacy and device autonomy. This involves tackling challenges related to resource-constrained environments, heterogeneous device capabilities, and maintaining security and privacy guarantees.

The project offers a unique opportunity to contribute to cutting-edge research with real-world impact. Successful outcomes will enable secure and private machine learning on IoT devices, fostering new applications in areas such as smart homes, industrial automation, and wearable health monitoring.

Responsibilities:

  • Literature review on decentralized federated learning, especially in relation to IoT and decentralized systems.
  • Design and development of decentralized FL frameworks suitable for constrained IoT devices.
  • Implementation and evaluation of the proposed framework using real-world datasets and testbeds.
  • Analysis of security and privacy aspects, along with resource utilization.
  • Documentation and presentation of findings in a thesis report, possibly leading to publications in top venues.

Requirements:

  • Enrollment in a Master's program in Computer Engineering, Computer Science, Electrical Engineering or related fields
  • Solid understanding of machine learning algorithms and frameworks (e.g., TensorFlow, PyTorch)
  • Proficiency in C and Python programming language
  • Experience with IoT devices and embedded systems development
  • Excellent analytical skills and a systematic problem-solving approach


Nice to Have:

  • Knowledge of cybersecurity and privacy principles
  • Familiarity with blockchain or other decentralized technologies
  • Interest in distributed computing and edge computing paradigms

Kontakt

Email: navid.asadi@tum.de

Betreuer:

Navidreza Asadi

Attacks on Cloud Autoscaling Mechanisms

Stichworte:
Cloud Computing, Kubernetes, autoscaling, low and slow attacks, Horizontal Pod Autoscaler (HPA), Vertical Pod Autoscaler (VPA), cloud security, container orches

Beschreibung

In the era of cloud-native computing, Kubernetes has emerged as a leading container orchestration platform, enabling seamless scalability and reliability for modern applications.

However, with its widespread adoption comes a new frontier in cybersecurity challenges, particularly low and slow attacks that exploit autoscaling features to disrupt services subtly yet effectively.

This project aims to delve into the intricacies of these attacks, examining their impact on Kubernetes' Horizontal Pod Autoscaler (HPA) and Vertical Pod Autoscaler (VPA), and proposing mitigation strategies for more resilient systems.

Responsibilities:

  • Conduct a thorough literature review to identify existing knowledge gaps and research on similar attacks.
  • Develop methodologies to simulate low and slow attack scenarios on Kubernetes clusters with varying configurations of autoscaling mechanisms.
  • Analyze the impact of these attacks on resource utilization, service availability, and overall system performance.
  • Evaluate current defense mechanisms and propose novel strategies to enhance the resilience of Kubernetes' autoscaling features.
  • Implement and test selected mitigation approaches in a controlled environment.
  • Document findings, present a comparative analysis of effectiveness, and discuss implications for future development in cloud security practices.


Requirements:

  • A strong background in computer engineering, computer science or a related field.
  • Familiarity with Kubernetes architecture and container orchestration concepts.
  • Experience in deploying and managing applications on Kubernetes clusters.
  • Proficiency in at least one scripting/programming language (e.g., Python, Go).
  • Understanding of cloud computing and cybersecurity fundamentals.


Nice to Have:

  • Prior research or hands-on experience in cloud security, particularly in the context of Kubernetes.
  • Knowledge of network protocols and low-level system interactions.
  • Experience with DevOps tools and practices.

 

Kontakt

Email: navid.asasdi@tum.de

Betreuer:

Navidreza Asadi

Working Student/Research Internship - On-Device Training on Microcontrollers

Beschreibung

We are seeking a highly motivated and skilled student to replicate a research paper that explores the application of pruning techniques for on-device training on microcontrollers. The original paper demonstrated the feasibility of deploying deep neural networks on resource-constrained devices, and achieved significant reductions in model size and computational requirements while maintaining acceptable accuracy.

Responsibilities:

  • Extend our existing framework by implementing the pruning techniques on a microcontroller-based platform (e.g., Arduino, ESP32)
  • Replicate the experiments described in the original paper to validate the results
  • Evaluate the performance of the pruned models on various benchmark datasets
  • Compare the results with the original paper and identify areas for improvement
  • Document the replication process, results, and findings in a clear and concise manner

Requirements:

  • Strong programming skills in C and Python
  • Experience with deep learning frameworks (e.g., TensorFlow, PyTorch) and microcontroller-based platforms
  • Familiarity with pruning techniques for neural networks is a plus
  • Excellent analytical and problem-solving skills
  • Ability to work independently and manage time effectively
  • Strong communication and documentation skills

 

Kontakt

Email: navid.asadi@tum.de

Betreuer:

Navidreza Asadi

Working Student - Machine Learning Serving on Kubernetes

Stichworte:
Machine Learning, Kubernetes, Containerization, Docker, Orchestration, Cloud Computing, MLOps, Machine Learning Operations, DevOps, Microservices Architecture,

Beschreibung

We are seeking an ambitious and forward-thinking working student to join our dynamic team working at the intersection of Machine Learning (ML) and Kubernetes. In this exciting role, you will be immersed in a cutting-edge environment where advanced ML models meet the power of container orchestration through Kubernetes. Your contributions will directly impact the development and optimization of scalable and robust ML serving systems leveraging the benefits of Kubernetes.

If you are a student passionate about both Machine Learning and Kubernetes, we invite you to join us on this exciting journey! We offer the chance to pioneer cutting-edge solutions that leverage the power of these two transformative technologies.

Responsibilities:

  • Collaborate with a cross-functional team to design and implement ML workflows on Kubernetes.
  • Assist in packaging and deploying ML models as microservices using containers (Docker) and managing them effectively through Kubernetes.
  • Optimize resource allocation, scheduling, and scaling strategies for efficient model serving at varying workloads.
  • Implement monitoring solutions specific to ML inference tasks within the Kubernetes cluster.
  • Troubleshoot and debug issues related to containerized ML applications
  • Document best practices, tutorials, and guides on leveraging Kubernetes for ML serving

Requirements:

  • Currently enrolled in a Bachelor's or Master's program in School of CIT
  • Strong programming skills in Python with experience in software development lifecycle methodologies.
  • Familiarity with machine learning frameworks such as TensorFlow and PyTorch.
  • Proficiency in container technologies. Docker and Kubernetes certification would be a plus but not mandatory.
  • Experience with cloud computing platforms; e.g., AWS, GCP or Azure.
  • Demonstrated ability to work independently with effective time management and strong problem-solving analytical skills.
  • Excellent communication and teamwork capabilities.

Nice to Have:

  • Kubernetes Certification: Having a valid Kubernetes certification (CKA, CKAD, or CKE) demonstrates your expertise in container orchestration and can be a significant advantage.
  • Experience with DevOps and/or MLOps Tools: Familiarity with MLOps tools such as MLflow, Kubeflow, or TensorFlow Extended (TFX) can help you streamline the machine learning workflow and improve collaboration. Experience with OpenTelemetry, Jaeger, Istio, and monitoring tools is a plus.
  • Knowledge of Distributed Systems: Understanding distributed systems architecture and design patterns can help you optimize the performance and scalability of your machine learning models.
  • Contributions to Open-Source Projects: Having contributed to open-source projects related to Kubernetes, machine learning, or MLOps demonstrates your ability to collaborate with others and adapt to new technologies.
  • Familiarity with Agile Methodologies: Knowledge of agile development methodologies such as Scrum or Kanban can help you work efficiently in a fast-paced environment and deliver results quickly.
  • Cloud-Native Application Development: Experience with cloud-native application development using frameworks like Cloud Foundry or AWS Cloud Development Kit (CDK) can be beneficial in designing scalable and efficient machine learning workflows.

 

Kontakt

Email: navid.asadi@tum.de

 

Betreuer:

Navidreza Asadi

Working Student for the Edge AI Testbed

Stichworte:
IoT, Edge Computing, Machine Learning, Measurement, Power Characterization

Beschreibung

We are seeking a highly motivated and enthusiastic Working Student to join our team as part of the Edge AI Testbed project. As a Working Student, a key member of our research team, you will contribute to the development and testing of cutting-edge Artificial Intelligence (AI) systems at the edge of the network. You will work closely with our researchers and engineers to design, implement, and evaluate innovative AI solutions that can operate efficiently on resource-constrained edge devices.

Responsibilities:

  • Assist in designing and implementing AI models for edge computing
  • Develop and test software components for the Edge AI Testbed
  • Collaborate with team members to integrate AI models with edge hardware platforms
  • Participate in performance optimization and evaluation of AI systems on edge devices
  • Contribute to the development of tools and scripts for automated testing and deployment
  • Document and report on project progress, results, and findings


If you are a motivated and talented student looking to gain hands-on experience in Edge AI, we encourage you to apply for this exciting opportunity!

Requirements:

  • Currently enrolled in a Bachelor's or Master's program in School of CIT
  • Strong programming skills in languages such as Python and C++
  • Experience with AI frameworks such as TensorFlow, PyTorch, or Keras
  • Familiarity with edge computing platforms and devices (e.g., Raspberry Pi, NVIDIA Jetson)
  • Basic knowledge of Linux operating systems and shell scripting
  • Excellent problem-solving skills and ability to work independently
  • Strong communication and teamwork skills


Nice to Have:

  • Experience with containerization using Docker
  • Familiarity with cloud computing platforms (e.g., Kubernetes)
  • Experience with Apache Ray
  • Knowledge of computer vision or natural language processing
  • Participation in open-source projects or personal projects related to AI and edge computing

 

Kontakt

Email: navid.asadi@tum.de

 

Betreuer:

Navidreza Asadi

An AI Benchmarking Suite for Microservices-Based Applications

Stichworte:
Kubernetes, Deep Learning, Video Analytics, Microservices
Kurzbeschreibung:
In the realm of AI applications, the deployment strategy significantly impacts performance metrics. This research internship aims to investigate and benchmark AI applications in two predominant deployment configurations: monolithic and microservices-based, specifically within Kubernetes environments. The central question revolves around understanding how these deployment strategies affect various performance metrics and determining the more efficient configuration. This inquiry is crucial as the deployment strategy plays a pivotal role in the operational efficiency of AI applications. Currently, the field lacks a comprehensive benchmarking suite that evaluates AI applications from an end-to-end deployment perspective. Our approach includes the development of a benchmarking suite tailored for microservice-based AI applications. This suite will capture metrics such as CPU/GPU/Memory utilization, interservice communication, end-to-end and per-service latency, and cache misses.

Beschreibung

In the realm of AI applications, the deployment strategy significantly impacts performance metrics.

This research internship aims to investigate and benchmark AI applications in two predominant deployment configurations: monolithic and microservices-based, specifically within Kubernetes environments.

The central question revolves around understanding how these deployment strategies affect various performance metrics and determining the more efficient configuration. This inquiry is crucial as the deployment strategy plays a pivotal role in the operational efficiency of AI applications.

Currently, the field lacks a comprehensive benchmarking suite that evaluates AI applications from an end-to-end deployment perspective. Our approach includes the development of a benchmarking suite tailored for microservice-based AI applications.

This suite will capture metrics such as CPU/GPU/Memory utilization, interservice communication, end-to-end and per-service latency, and cache misses.

 

 

Voraussetzungen

  • Familiarity with Kubernetes
  • Familiarity with Deep Learning frameworks (e.g., PyTorch or TensorFlow)
  • Basics of computer networking

 

Kontakt

Email: navid.asadi@tum.de

 

Betreuer:

Navidreza Asadi

Performance Evaluation of Serverless Frameworks

Stichworte:
Serverless, Function as a Service, Machine Learning, Distributed ML

Beschreibung

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.

 Requirements:

  • Familiarity with Kubernetes
  • Basics of computer networking

 

 

Kontakt

Email: navid.asadi@tum.de

 

Betreuer:

Navidreza Asadi

Investigation of Flexibility vs. Sustainability Tradeoffs in 6G

Beschreibung

5G networks brought significant performance improvements for different service types like augmented reality, virtual reality, online gaming, live video streaming, robotic surgeries, etc., by providing higher throughput, lower latency, higher reliability as well as the possibility to successfully serve a large number of users. However, these improvements do not come without any costs. The main consequence of satisfying the stringent traffic requirements of the aforementioned applications is excessive energy consumption.

Therefore, making the cellular networks sustainable, i.e., constraining their power consumption, is of utmost importance in the next generation of cellular networks, i.e., 6G. This goal is of interest mostly to cellular network operators. Of course, while achieving network sustainability, the satisfaction of all traffic requirements, which is of interest to cellular users, must be ensured at all times. While these are opposing goals, a certain balance has to be achieved.

In this thesis, the focus is on the type of services known as eMBB (enhanced mobile broadband). These are services that are characterized as latency-tolerant to a certain extent, but sensitive to the throughput and its stability. Live video streaming is a use case falling into this category. For these applications, on the one side, higher data rates imply higher energy consumption. On the other side, the users can be satisfied with slightly lower throughput as long as the provided data rate is constant, which corresponds to the flexibility that the network operator can exploit. Hence, the question that needs to be answered in this thesis is what is the optimal trade-off between the data rate and the energy consumption in a cellular network with eMBB users? To answer this question, the entire communication process will be encompassed, i.e., from the transmitting user through the base station and core network to the receiving end. The student will need to formulate an optimization problem to address the related problem, which they will then solve through exact optimization solvers, but also through proposing simpler algorithms (heuristics) that reduce the solution time while not considerably deteriorating the system performance.

Voraussetzungen

  • Good knowledge of any programming language
  • Good mathematical and analytical thinking skills
  • High level of self-engagement and motivation

Kontakt

valentin.haider@tum.de

fidan.mehmeti@tum.de

Betreuer:

Valentin Haider, Fidan Mehmeti

Intel's IPU: Starting from the beginning

Beschreibung

Intel develops Network Devices consisting of an FPGA and a general purpose processor. These are the so called IPUs. The goal of this Thesis/Position is to get such an IPU (Intel IPU F2000X) up and running and evaluates its potential. Here, the goal is to program a custom IPU application and evaluate metrics like latency, throughput, and many more under varying circumstances.

Voraussetzungen

  • Basic Knowledge Linux Terminal
  • Basic Knowledge C/C++
  • Basic Knowledge of and about FPGAs

Betreuer:

DPU as Measurement Cards and Load Generators

Beschreibung

Datacenters experience higher and more demanding Network Loads and Traffic. Companies like Nvidia developed special networking hardware to fulfill these demands (The Nvidia Bluefield Line-Up). These cards promise high throughput and high precision. The features required to achieve such tasks can also be used to use Bluefield Cards as potential measurement cards or as load generators.

The goal of this Thesis/Position is to evaluate the performance and feasibility of this approach

For more information, please contact me directly (philip.diederich@tum.de)

Voraussetzungen

  • Basic Knowledge Linux Terminal
  • Basic Knowledge Python
  • Basic Knowledge C/C++

Betreuer:

Advancing Real-time Network Simulations to Real World Behaviour

Beschreibung

Testing real-time application and networks is very timing sensitive. It is very hard to get this precision and accuracy in the real-world. However, the real-world itself also behaves different then simualtions. Our Simulator behaves like the theory dictates and allows us to get these precise timing, but needs to be tested and exteded to behave more like a real-network would

 

Requirements

  • Knowledge of NS-3
  • Knowledge of Python
  • Knowledge of C/C++

 

Please contact me for more information (philip.diederich@tum.de)

Betreuer:

Working Student - Real-Time Network Controller for Research

Beschreibung

Chameleon is a real-time network controller that guarantees packet latencies for admitted flows. However, Chameleon is designed to work in high performance environments. For research and development, a different approach that offers more debugging and extension capablites would suit us better.

Goals:

  • Create Real-time Network Controller
  • Controller needs to be easy to debug
  • Controller needs to be easy to extend
  • Controller needs to have good logging and tracing

 

Requirements:

  • Advanced Knowledge of C/C++
  • Advanced Knowledge of Python

 

Please contact me for more information (philip.diederich@tum.de)

 

Amaury Van Bemten, Nemanja Ðeri?, Amir Varasteh, Stefan Schmid, Carmen Mas-Machuca, Andreas Blenk, and Wolfgang Kellerer. 2020. Chameleon: Predictable Latency and High Utilization with Queue-Aware and Adaptive Source Routing. In The 16th International Conference on emerging Networking EXperiments and Technologies (CoNEXT ’20), December 1–4, 2020, Barcelona, Spain. ACM, New York, NY, USA, 15 pages. https://doi.org/10.1145/3386367. 3432879

Betreuer:

Controlling Stochastic Network Flows for Real-time Networking

Beschreibung

Any data that is sent in a real-time network is monitored and accounted for. This allows us with the help of some mathematical frameworks to calculate upper bounds for the latency of the flow. These frameworks and controllers often consider hard real-time guarantees. This means that every packet arrives in time every time. With soft real-time guarantees, this is not the case. Here, we are allowed to have some leeway

In this thesis, we want to explore how we can model and admit network flows that have a stochastical nature.

 

Please contact me for more information (philip.diederich@tum.de)!!

Betreuer:

Working Student: Framework for Testing Realtime Networks

Beschreibung

Testing a Network Controller, custom real-time protocols, or verifying simulations with emulations requires a lot of computing effort. This is why we are developing a framework that helps you run parallel networking experiments. This framework also increases the reproducibility of any networking experiment.

The main Task of this position is to help develop the general-purpose framework for executing parallel networking experiments.

Tasks:

  • Continue developing the Framework for multi server / multi app usage
  • Extend Web Capabilities of the Framework
  • Automate Starting and Stopping
  • Ease-of-use Improvements
  • Test the functionality

 

Requirements:

  • Knowledge of Python
  • Basic Knowledge of Web-App Development (FastApi, React etc...)
  • Basic Knowledge of System Architecture Development

 

Feel free to contact me per mail (philip.diederich@tum.de)

Betreuer:

Working Student Infrastructure Service Management

Beschreibung

We are seeking a highly motivated and detail-oriented Working Student to join our data center team. As a Working Student, you will assist in the daily operations of our data center, gaining hands-on experience in a fast-paced and dynamic environment.

Responsibilities:

  Assist with regular data center tasks, such as.

  • Rack and Stack equipment
  • Cable Management and organization
  • Perform basic troubleshooting and maintenance tasks
  • Assist with inventory management

 

  • Monitor data center systems and report any discrepancies or issues
  • Create the basis for our Data Center Infrastructure Management
  • Develop and maintain documentation of data center procedures and policies
  • Perform other duties as required to support the data center operations

Requirements

 

  • Availability to work 8 - 10 hours per week with flexible scheduling to accommodate academic commitments
  • Basic knowledge of computer systems, networks, and data center operations
  • Basic knowledge in Python

 

Betreuer:

Development of a GUI for Monitoring and Debugging a Digital Twin of QKD Networks

Stichworte:
GUI
Kurzbeschreibung:
Quantum key distribution (QKD) is a promising technology for providing secure communication also in the presence of powerful quantum computers. Due to its time-dependent behavior and multi-layer architecture, analysis of routing policies and network performance parameters can be done by emulation. Our implemented network emulator based on container and network function virtualization allows network performance parameters analysis and routing policy optimization.

Beschreibung

We search for a student to build a GUI, simplifying analysis and interaction with the network emulator. The emulator is based on Containernet and includes QKD-specific network function virtualization. Currently, distributed routing is supported but will be extended by centralized routing. Monitoring data from active QKD-links are fed in to mirror realistic circumstances.

  • Build a front-end displaying performance and operational data
  • Build a GUI for dynamically changing secret key rates 

Voraussetzungen

  • Programming skills in Python
  • Experience in front-end web development
  • Interest in security and practical concepts of guaranteed security

 

Kontakt

Mario Wenning mario.wenning@tum.de

Betreuer:

Mario Wenning

Distributed Deep Learning for Video Analytics

Stichworte:
Distributed Deep Learning, Distributed Computing, Video Analytics, Edge Computing, Edge AI

Beschreibung

In recent years, deep learning-based algorithms have demonstrated superior accuracy in video analysis tasks, and scaling up such models; i.e., designing and training larger models with more parameters, can improve their accuracy even more.

On the other hand, due to strict latency requirements as well as privacy concerns, there is a tendency towards deploying video analysis tasks close to data sources; i.e., at the edge. However, compared to dedicated cloud infrastructures, edge devices (e.g., smartphones and IoT devices) as well as edge clouds are constrained in terms of compute, memory and storage resources, which consequently leads to a trade-off between response time and accuracy. 

Considering video analysis tasks such as image classification and object detection as the application at the heart of this project, the goal is to evaluate different deep learning model distribution techniques for a scenario of interest.

Kontakt

Email: navid.asadi@tum.de

 

Betreuer:

Navidreza Asadi

Edge AI in Adversarial Environment: A Simplistic Byzantine Scenario

Stichworte:
Distributed Deep Learning, Distributed Computing, Byzantine Attack, Adversarial Inference

Beschreibung

This project considers an environment consisting of several low performance machines which are connected together across a network. 

Edge AI has drawn the attention of both academia and industry as a way to bring intelligence to edge devices to enhance data privacy as well as latency. 

Prior works investigated on improving accuracy-latency trade-off of Edge AI by distributing a model into multiple available and idle machines. Building on top of those works, this project adds one more dimension: a scenario where $f$ out of $n$ contributing nodes are adversary. 

Therefore, for each data sample an adversary (1) may not provide an output (can also be considered as a faulty node.) or (2) may provide an arbitrary (i.e., randomly generated) output.

The goal is to evaluate robustness of different parallelism techniques in terms of achievable accuracy in presence of malicious contributors and/or faulty nodes.

Note that contrary to the mainstream existing literature, this project mainly focuses on the inference (i.e., serving) phase of deep learning algorithms, and although robustness of the training phase can be considered as well, it has a much lower priority.

Kontakt

Email: navid.asadi@tum.de

 

Betreuer:

Navidreza Asadi

On the Efficiency of Deep Learning Parallelism Schemes

Stichworte:
Distributed Deep Learning, Parallel Computing, Inference, AI Serving

Beschreibung

Deep Learning models are becoming increasingly larger so that most of the state-of-the-art model architectures are either too big to be deployed on a single machine or cause performance issues such as undesired delays.

This is not only true for the largest models being deployed in high performance cloud infrastructures but also for smaller and more efficient models that are designed to have fewer parameters (and hence, lower accuracy) to be deployed on edge devices.

That said, this project considers the second environment where there are multiple resource constrained machines connected through a network. 

Continuing the research towards distributing deep learning models into multiple machines, the objective is to generate more efficient variants/submodels compared to existing deep learning parallelism algorithms.  

Note that this project mainly focuses on the inference (i.e., serving) phase of deep learning algorithms, and although efficiency of the training phase can be considered as well, it has a much lower priority.

Kontakt

Email: navid.asadi@tum.de

 

Betreuer:

Navidreza Asadi

Optimizing Distributed Deep Learning Inference

Stichworte:
deep learning, distributed systems, parallel computing, model parallelism, communication overhead reduction, performance evaluation, edge devices

Beschreibung

The rapid growth in size and complexity of deep learning models has led to significant challenges in deploying these architectures across resource-constrained machines interconnected through a network. This research project focuses on optimizing the deployment of deep learning models at the edge, where limited computational resources and high-latency networks hinder performance. The main objective is to develop efficient distributed inference techniques that can overcome the limitations of edge devices, ensuring real-time processing and decision-making.

The successful candidate will work on addressing the following challenges:

  • Employing model parallelism techniques to distribute workload across compute nodes while minimizing communication overhead associated with exchanging intermediate tensors between nodes.
  • Reducing inter-operator blocking to improve overall system throughput.
  • Developing efficient compression techniques tailored for deep learning data exchanges to minimize network latency.
  • Evaluating the performance of proposed modifications using standard deep learning benchmarks and real-world datasets.

 

Responsibilities:

  • Implement and evaluate various parallelism techniques, such as model parallelism and variant parallelism, from a communication efficiency perspective.
  • Identify and implement mechanisms to minimize the exchange of intermediate tensors between compute nodes, potentially using advanced compression techniques tailored for deep learning data exchanges.
  • Conduct comprehensive performance evaluations of proposed modifications using standard deep learning benchmarks and real-world datasets. Assess improvements in latency, resource efficiency, and overall system throughput compared to baseline configurations.
  • Write technical reports and publications detailing the research findings.

Requirements:

  • Pursuing a Master's degree in School of CIT
  • Strong background in deep learning, distributed systems, and parallel computing.
  • Proficiency in Python and experience with deep learning frameworks (e.g., TensorFlow, PyTorch).
  • Excellent problem-solving skills and the ability to work independently and collaboratively as part of a team.
  • Strong communication and writing skills for technical reports and publications.

 

Kontakt

Email: navid.asadi@tum.de

Betreuer:

Navidreza Asadi

Bachelorarbeiten

Development of a tool to evaluate robustness surfaces for networks

Stichworte:
robustness surface, resilience

Beschreibung

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.

 

Voraussetzungen

C++, Python

Kontakt

shakthivelu.janardhanan@tum.de

Betreuer:

Shakthivelu Janardhanan

Distributed LLM Serving on Constrained Edge Devices

Stichworte:
Distributed Deep Learning, Parallel Computing, Inference, Communication Efficiency, Large Language Models (LLM)

Beschreibung

The increasing demand for Natural Language Processing (NLP) tasks has led to the development of Large Language Models (LLMs). However, their high memory requirements have limited their deployment on Edge and IoT devices. To address this challenge, multiple distributed LLM frameworks have emerged.

This project aims to benchmark and compare the performance of existing frameworks on Edge and IoT devices. We will evaluate their ability to optimize resource utilization, minimize latency, and provide cost-effective execution of LLMs on devices with limited compute resources.

The goal is to identify the strengths and weaknesses of each framework, including their scalability, reliability, and fault tolerance in the face of network disruptions and device failures. 

Betreuer:

Navidreza Asadi

PyRBD: Development of a C++ backend for Reliability Block Diagram evaluation

Stichworte:
Reliability block diagram, availability

Beschreibung

A reliability block diagram is a tool used to measure the availability of a system (a network, in our case). However, the existing tools as software packages do not work with bidirectional links. 

 

This work aims to build a tool that can evaluate the availability of a network based on the RBD. The back end should be in C++. This back end should be wrapped in a Python function.

Voraussetzungen

Proficient in C++,
Basic knowledge of Python Ctype bindings.

Kontakt

shakthivelu.janardhanan@tum.de

Betreuer:

Shakthivelu Janardhanan

Implementation and Stochastic Evaluation of a Chemical Reaction Network for Successive Interference Cancellation in Molecular Communication Networks

Beschreibung

Molecular communication (MC) is a novel communication paradigm envisioned to enable revolutionary future medical and biological use cases such as in-body networks for the diagnosis and treatment of diseases. MC is based on the transport of molecules for information exchange and represents a very energy-efficient and bio-compatible communication mechanism on the centimeter to nanometer scale. The communication nodes can be very small as they will be based on artificial cells or other types of tiny nano-machines.

In order to realize complex applications, such as targeted drug delivery or the detection and localization of infections and tumors, nano-machines must cooperate and communicate. The specific properties and mechanisms in biological environments and at very small scales lead to several challenges:

  • Novel channel models and conditions based on diffusion and flow of molecules.
  • Extremely slow speeds compared to electromagnetic waves.
  • Highly stochastic behavior of the molecules.
  • Low capability of future nano-machines, not able to conduct complex computations or sophisticated algorithms.

Therefore, research on MC networks is crucial to enable a future internet of bio-nano things (IoBNT) integrating classical and molecular networks.

 

In this thesis, the student will work on the topic of chemical reaction networks (CRNs), which represent a possible substrate for computations and programmability in biological systems. A CRN is built from a number of coupled chemical reactions and is designed to turn a certain concentration of input molecules into a concentration of output molecules.

The student will be tasked with implementing a CRN that approximates a real signal processing algorithm, namely successive interference cancellation (SIC). SIc could be used, for example, to realize non-orthogonal multiple access schemes in a larger MC network. 

The CRN will be designed conceptually and implemented using Python. Then, the CRN will be evaluated rigorously using both deterministic solvers based on differential equations, as well as stochastic simulations that take into account individual random molecule interactions.

Kontakt

alexander.wietfeld@tum.de

Betreuer:

Alexander Wietfeld

_Bachelor‘s Thesis Autoencoder Optimized Error Concealment for Semantic Video Conferencing

Beschreibung

Semantic communication enables communication of discrete symbols. Even when a proportion of symbols are lost, an appropriate synthesis of the intended meaning is possible.

Error concealment attempts to minimize the impact of errors (symbol loss), by approximating lost symbols.

This thesis applies machine-learning to the hypothesis that:
If semantic symbols are lost, given first order motion model video conferencing, then, with the aid of mutual information, temporal information, and the structure of semantic symbols, machine learning can be used to create an error concealment technique more performant than an algorithmic technique, because the patterns in the data are more complex than easily captureable algorithmically.

Betreuer:

Alexander Griessel

Handover with PMIPv6 in LDACS

Beschreibung

This thesis will focus on the next generation air to ground communication standard: LDACS. It specifically discusses the IP Layer of the LDACS and mobility mechanisms behind it which enable a seamless handover for the aircraft.

 

Betreuer:

Anna Prado, Hansini Vijayaraghavan - Thomas Richter (Rohde&Schwarz)

Implementation and Evaluation of a Particle-Based Simulator for Molecular Communication with Diffusion and Flow

Beschreibung

Implement a particle-based simulation framework for molecular communication networks:

 

 

Use e.g. Python or MATLAB

 

Main target scenario: cylindrical tube with multiple transmitters and receivers

 

Effects: Diffusion, laminar/uniform flow -> output: particle trajectories

 

Enable different types of transmitters and receivers (e.g. point, cross-sectional distribution, volume) Flexibility in placement of TX and RX and shape of the initial molecules distribution  

 

Implement and evaluate a non-orthogonal multiple access scheme based on the distance and the emitted number of molecules from each TX

Kontakt

alexander.wietfeld@tum.de

Betreuer:

Alexander Wietfeld

Experimental Evaluation of xApp-related Vulnerabilities in the O-RAN's RAN Intelligent Controller Implementation

Stichworte:
O-RAN, Security, RAN Intelligent Controller

Beschreibung

In previous mobile network generations, Radio Access Networks (RAN) have been treated as a proprietary, closed network segment that is specific to every operator. To accelerate development and innovation, new initiatives such as the O-RAN ALLIANCE were born, aiming to split the RAN into different components and standardize the open interfaces that connect them.

 

Fundamentally, O-RAN leverages the concept of Software Defined RAN (SD-RAN) by decoupling the RAN data plane from the control plane and introducing several new RAN-controlling components. One of the central components is the near real-time RAN Intelligent Controller (nearRT-RIC), which manages the RAN (network slices, handovers, etc). The nearRT-RIC is designed to allow both the use of traditional, rule-based policies and Machine Learning or data-driven ones to optimize the RAN operation. The logic of these policies is encapsulated in applications called xApps that run on the nearRT-RIC platform and can read and modify different parameters of the RAN.

 

While providing opportunities for efficient resource management, the nearRT-RIC is also a prospective target for attackers, because of its control power over the RAN. Specifically, an attack vector is a malicious xApp that can interfere with other legitimate xApps running on the nearRT-RIC.  

 

NearRT-RIC implementations are still in their infancy and suffer from bugs and security vulnerabilities. These vulnerabilities are also prevalent in open-source implementations such as O-RAN Software Community's (OSC) RIC [1], where malicious xApps may disrupt the nearRT-RIC operation. The H Release of the OSC nearRT-RIC suffers from two major vulnerabilities that can compromise the operation of the RIC and crash it [2]. Additionally, a crafted packet sent by an xApp can crash memcpy and implicitly the whole OSC nearRT-RIC [3]. Such vulnerabilities significantly hinder the wide-scale adoption and deployment of O-RAN.

Objectives

The goal of this student thesis is to reproduce the attacks discussed in [2] and [3] for the newer OSC nearRT-RIC I Release. Additionally, after reproducing the existing attacks and understanding the OSC RIC Platform, the student is expected to explore new attack attempts with the same goal of disrupting OSC nearRT-RIC. Special focus will be put on the critical components of the system, such as the Subscription Manager and Subscription Procedures, Routing Message Router, other xApps, and O1/A1/E2 Terminations.

 

---

[1] “O-RAN SC Projects,” https://docs.o-ran-sc.org/en/latest/projects.html#near-realtime-ran-intelligent-controller-ric, accessed: 2024-04-19.

[2] Hung, C.F., Chen, Y.R., Tseng, C.H., & Cheng, S.M. (2024). Security Threats to xApps Access Control and E2 Interface in O-RAN. IEEE Open Journal of the Communications Society, 5, 1197-1203.

[3] "Opening Critical Infrastructure: The Current State of Open RAN Security,” https://www.trendmicro.com/en us/research/23/l/the-current-state-of-open-ran-security.html, accessed: 2024-04-19.

 

Voraussetzungen

- Experience with Docker and Kubernetes

- Linux Knowledge

- C/C++ Knowledge is a plus

Kontakt

- Razvan-Mihai Ursu (razvan.ursu@tum.de)

Betreuer:

Razvan-Mihai Ursu

Towards Improving Class Parallelism for Edge Environments

Stichworte:
Distributed ML, Parallel Computing, CNN, Deep Learning

Beschreibung

Main-stream serving paradigms for distributed models, such as data parallelism and model parallelism, are not suitable when it comes to inference for tasks that require low latency and have atomic input streams. A recent effort, Sensai, proposes a new generic approach called class parallelism that aims to distribute a base convolution neural network (CNN) model across several homogeneous machines.

    The model distribution paradigm decomposes a CNN into disconnected subnets, each responsible for predicting specific classes or groups of classes. They claim that this approach enables fast, in-parallel inference on live data with minimal communication overhead, significantly reducing inference latency on single data items without compromising accuracy.

    Class Parallelism, however, comes with its own set of challenges and limitations. For instance, since the generated models should be created in a homogeneous manner; they share similar characteristics. Further, regardless of the input, all sub-models have to be executed to get the final prediction, which directly impacts the robustness and scalability of the system.

    During the first stage of the thesis, our goal is to reproduce the results from the paper. Later, we want to improve the existing method to become more robust and possibly extend it to new use cases besides image classification. Finally, if time permits, we want to evaluate the trained models in an edge environment.

Betreuer:

Navidreza Asadi

Masterarbeiten

Optimal Placement of MAF Chains with Priorities

Beschreibung

Optimal Placement of MAF chains considering Priority

Betreuer:

Nicolai Kröger

Scaling and Model Disaggregating Distributed ML Systems: Monolithic vs. Microservices Performance Analysis

Stichworte:
Kubernetes, Deep Learning, Video Analytics, Microservices

Beschreibung

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.

Betreuer:

Navidreza Asadi

Finding Anti-Patterns on Microservices-Based AI Applications

Stichworte:
Machine Learning, Kubernetes, Microservices

Beschreibung

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.

Betreuer:

Navidreza Asadi

Formulation of Generalized System and Radio Requirements for Vehicle Access Systems

Beschreibung

Channel Description for Wireless Access Systems.

Betreuer:

Nicolai Kröger - (Mercedes-Benz AG)

Optical Access Networks Dependability on the Electrical Distribution Networks

Stichworte:
Optical Access Networks
Kurzbeschreibung:
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.

Beschreibung

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.

Voraussetzungen

Knowledge of:

  • Python
  • Object Oriented Programming
  • GIT
  • Optical Networks
  • Linux

Kontakt

cristian.bermudez-serna@tum.de

Betreuer:

Cristian Bermudez Serna

Implementation and Evaluation of MPTCP for Access Traffic Steering, Switching, and Splitting in 5G

Beschreibung

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.

 

 

Voraussetzungen

  • Experience with programming in C/C++
  • Strong foundation in wireless networking concepts
  • Motivation to learn 5G concepts
  • Availability to work in-presence

Betreuer:

Data-driven Infrastructure Monitoring Framework for Distributed Fiber Sensing

Beschreibung

This thesis focuses on developing and evaluating a practical approach to phase-sensitive OTDR measurement analysis. An experimental evaluation setup including an OTDR unit capable of measuring phase-sensitive Rayleigh Scattering as well as Brillouin Scattering and compute and memory limited processor provides the basis. The work aims to answer the following questions:

  • How do we achieve real-time visualization of the measurement results?
  • How do we enable automated (near) real-time OTDR measurement analysis, i.e., event detection and identification?
  • Can a software that does data acquisition, event detection and display be deployed directly on-board the DFOS device that has low computing power and memory? How do we minimize the hardware requirements concerning compute power, memory and storage?

 

Betreuer:

Jasper Konstantin Müller - Jasper Müller (Adtran Networks SE)

Investigating the Dynamic Migration of Medical Applications in the Network

Beschreibung

 

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.

 

Voraussetzungen

 

·       Motivation

 

·       Ideally some experience in solving optimization problems

 

·       Basic networking knowledge

 

·       Basic programming skills

 

Betreuer:

Nicolai Kröger, Fidan Mehmeti

Analysis and Optimization of Fiber-to-the-Room MAC protocols

Kurzbeschreibung:
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.

Beschreibung

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.

Kontakt

cristian.bermudez-serna@tum.de

Betreuer:

Cristian Bermudez Serna - Christian Bluemm (Huawei)

Analysing the 5G Roaming Control Plane Connections and Evaluating their Security Capabilities

Stichworte:
5G, Roaming, Core, Network Functions, IPX, SEPP, PRINS

Beschreibung

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.

A major part of both roaming modes 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.

Two SEPPs connections are divided into the N32-c and N32-f interfaces. Via N32-c, the connection is established and the security capabilities of N32-f are negotiated. All control messages between NFs of the visited and the home PLMN are transmitted via N32-f. While N32-c is secured with an end-to-end Transport Layer Security (TLS) connection, N32-f either uses the same security or, alternatively, a new 5G protocol named PRotocol for N32 INterconnect Security (PRINS). PRINS uses end-to-end application layer encryption and additionally hop-to-hop TLS encryption. While one direct TLS connection is more secure, it relies on a direct link between both parties. Considering a roaming scenario with two countries separated by multiple thousand kilometres, direct links are not always feasible. Alternatively, two PLMNs are connected via IP Exchange Networks (IPXs). To be able to route the packets reliably to their respective destinations, the IPX providers have to have access to the packets’ data. PRINS aims to provide security for this option by using the Javascript Object Signing and Encryption (JOSE) framework.

 

This work aims to implement N32-c and both options for the N32-f interface and investigate their differences regarding security, operability, and performance.

Voraussetzungen

Basic understanding of 5G networks advantageous; especially of the 5G core network

– interest and motivation to learn the system are sufficient

 

  • Programming knowledge in C useful (for Open5GS)
  • Interest in roaming functionalities and their security

Kontakt

Oliver Zeidler (oliver.zeidler@tum.de)

Betreuer:

Oliver Zeidler

Adding links to improve sovereignty

Stichworte:
sovereignty, adding links

Beschreibung

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

Voraussetzungen

Communication Network Reliability course, Python, Integer Linear Programming

Kontakt

shakthivelu.janardhanan@tum.de

Betreuer:

Shakthivelu Janardhanan

Joint optimization of network sovereignty and availability

Stichworte:
availability, reliability, Minimal cut set

Beschreibung

A cut set is a set of components that, by failing, causes the system to fail. A cut set is minimal if it cannot be reduced without losing its status as a cut set.

In this work, we aim to improve network availability and sovereignty based on the mincutsets. We employ graph coloring methods to improve the availability of mincutsets.

 

Voraussetzungen

Mandatory: Python
Communication Network Reliability course, and Integer Linear Programming.

Kontakt

shakthivelu.janardhanan@tum.de

Betreuer:

Shakthivelu Janardhanan

Optimizing the Availability of Medical Applications

Beschreibung

 

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.

 

Voraussetzungen

 

·       Motivation

 

·       Ideally some experience in solving optimization problems

 

·       Basic networking knowledge

 

·       Basic programming skills

 

Betreuer:

Nicolai Kröger, Fidan Mehmeti

Minimizing the Power Consumption of Medical Applications

Beschreibung

 

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.

 

Voraussetzungen

 

·       Motivation

 

·       Ideally some experience in solving optimization problems

 

·       Basic networking knowledge

 

·       Basic programming skills

 

Betreuer:

Nicolai Kröger, Fidan Mehmeti

In-Network Placement of Medical Applications

Beschreibung

 

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.

 

Voraussetzungen

 

·       Motivation

 

·       Ideally some experience in solving optimization problems

 

·       Basic networking knowledge

 

·       Basic programming skills

 

Betreuer:

Nicolai Kröger, Fidan Mehmeti

Implementing and Evaluating 5G Roaming Scenarios in an Open Source Testbed

Stichworte:
5G, Roaming, Core Network, Network Functions

Beschreibung

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.

Voraussetzungen

• Basic understanding of 5G networks advantageous; especially of the 5G core network

  • interest and motivation to learn the system are sufficient

• Programming knowledge in C useful (for Open5GS)

• Interest in Roaming functionalities

• Interest in security would be nice, but is not needed (not the main focus of the work

Kontakt

Oliver Zeidler (oliver.zeidler@tum.de)

Julian Sturm (julian.sturm@tum.de)

Betreuer:

Oliver Zeidler

Combined Scheduling of PSFP and TAS

Stichworte:
TSN, TAS, PSFP
Kurzbeschreibung:
Develop and implemented an algorithm to define a combined TAS and PSFP schedule.

Beschreibung

Time Sensitive Networking (TSN) provides a variety of different mechanisms providing real-time communication. Especially, TSN is able to transmit periodic time-triggered traffic with strict real-time requirements.

This thesis focuses on the time-aware shaper (TAS) standardized in IEEE 802.1Qbv and the per-stream filtering and policing (PSFP) mechanism defined in IEEE 802.1Qci. The goal is to develop an algorithm combining a TAS and a PSFP schedule. The TAS schedule should be secured by a time-based PSFP schedule. The PSFP schedule should drop frames or reduce their priority which are not matching the expected arrival interval.
The algorithm has to be evaluated in a testbed considering traffic scenarios with multiple time-triggered streams.

Betreuer:

Laura Becker, Yash Deshpande - Manuel Eppler (Siemens AG)

VM Selection for Financial Exchanges in the Cloud

Stichworte:
Cloud Computing, Financial Exchange, Fairness, Subset Selection

Beschreibung

Financial exchanges consider a migration to the cloud for scalability, robustness, and cost-efficiency. Jasper presents a scalable and fair multicast solution for cloud-based exchanges, addressing the lack of cloud-native mechanisms for such.

To achieve this, Jasper employs an overlay multicast tree, leveraging clock synchronization, kernel-bypass techniques, and more. However, there are opportunities for enhancement by confronting the issue of inconsistent VM performance within identical instances. LemonDrop tackles this problem, detecting under-performing VMs in a cluster and selecting a subset of VMs optimized for a given application's latency needs. Yet, we believe that LemonDrop's approach of using time-expensive all-to-all latency measurements and an optimization routine for the framed Quadratic Assignment Problem (QAP) is overly complex. 

The proposed work aims to develop a simpler and scalable heuristic, that achieves reasonably good results within Jasper's time constraints. 

Kontakt

Email: navid.asadi@tum.de

 

Betreuer:

Navidreza Asadi

Towards Improving Model Generation in Variant Parallelism

Stichworte:
Distributed Deep Learning, Parallel Computing, Inference, Communication Efficiency

Beschreibung

Resource constraints of edge devices serve as a major bottleneck when deploying large AI models in edge computing scenarios. Not only are they difficult to fit into such small devices, but they are also quite slow in inference time, given today's need for rapid decision-making. One major technique developed to solve this issue is Variant Parallelism. In this ensemble-based deep-learning distribution method, different main model variants are created and deployed in separate machines, and their decisions are combined to produce the final output. 

    The method provides graceful degradation in the presence of faulty nodes or poor connectivity while achieving an accuracy similar to the base model.

    However, the technique used to generate variants can fail in scalability as combining variants of smaller size with somewhat identical characteristics may not help achieve a significant accuracy boost unless they are retrained with different random seeds. Therefore, this research will focus on improving variant parallelism by exploring other ways to generate variants. We will apply knowledge distillation (KD), where a teacher model of a certain type (e.g., ResNet-50) can be used to train a smaller student model or a model of a completely different structure (e.g., MobileNet). 

    We aim to develop a variant generation technique where we can generate as many variants as there are participating devices while boosting accuracy and inference speed. Additionally, we will create an optimization scenario that dynamically creates a smaller student model based on specific requirements, such as hardware characteristics and end-to-end performance metrics.

Betreuer:

Navidreza Asadi

Possibilities of Localization Mechanisms in a 5G Lab Environment

Beschreibung

Mobile networks have long provided mechanisms for localization. This capability has been improved with LTE and new features in 5G allow even better positioning.

While some positioning methods are hard to recreate in a lab environment (such as AoA), others are possible (e.g. E-CID). One goal is to identify which can be recreated on-site.

Additionally, not much is known about the prevalence of support for these localization mechanisms.

According to their documentation, the Amarisoft Callbox supports the NL1-Interface between an external LMF and the built-in AMF. This can be used for an early prototype.

Minimum goals:

·         Implement LMF that is able to interact with Amarisoft Callbox over NL1

·         Evaluate which localization methods are suitable for lab-based testing

·         Evaluate the prevalence of advertised localization mechanisms in commercial UEs

·         Evaluate the implementation status of localization mechanisms in commercial UEs

·         Evaluate if results can be explained by OS, Baseband or other factors

·         Find and evaluate possible attacks on the UEs location privacy

 

Extended goals:

·         Implement LPP into Open5GS with AmariRAN or Open5GS with OAI

·         Implement Demo into the 5GCube framework

Betreuer:

Oliver Zeidler - Julian Sturm ()

Planning and Evaluation of Unbalanced and Balanced PON for Rural Areas

Stichworte:
Optical Access Network
Kurzbeschreibung:
With the increasing need for broadband in rural areas and the shift towards fiber-based Passive Optical Networks (PON), this research will focus on the deployment strategies of Balanced PON (BPON) and Unbalanced PON (UPON). The aim is to enhance efficiency and minimize infrastructure costs associated with broadband deployment. Recognizing the high expense associated with fiber deployment, especially in rural areas where geographical and demographic factors pose significant challenges, this study will focus on a shift from the conventional BPON approach, characterized by uniform power splitting (e.g., 1:16 or 1:32 splitting), to a more adaptable UPON strategy. The UPON architecture facilitates variable power splitting ratios, enhancing network reach and optimizing the distribution of network resources—such as bandwidth and optical power—in rural areas, where the distances between Optical Network Units (ONUs) or customer premises are greater than those in urban settings.

Beschreibung

With the increasing need for broadband in rural areas and the shift towards fiber-based Passive Optical Networks (PON), this research will focus on the deployment strategies of Balanced PON (BPON) and Unbalanced PON (UPON). The aim is to enhance efficiency and minimize infrastructure costs associated with broadband deployment. Recognizing the high expense associated with fiber deployment, especially in rural areas where geographical and demographic factors pose significant challenges, this study will focus on a shift from the conventional BPON approach, characterized by uniform power splitting (e.g., 1:16 or 1:32 splitting), to a more adaptable UPON strategy. The UPON architecture facilitates variable power splitting ratios, enhancing network reach and optimizing the distribution of network resources—such as bandwidth and optical power—in rural areas, where the distances between Optical Network Units (ONUs) or customer premises are greater than those in urban settings.

The methodology includes gathering detailed rural area data from OpenStreetMap to simulate realistic network designs, including the strategic placement of Optical Line Terminals (OLTs), splitters, and Optical Network Units (ONUs). The research will compare the traditional BPON, both single and cascading splitting, against UPON in terms of fiber length utilization, network elements placement strategy, power distribution efficiency, and overall cost-effectiveness. By using Gabriel graphs to generate rural area networks and analyzing PON equipment parameters like transmitted power range, sensitivity, and fiber attenuation, this research will be dedicated to identifying the most efficient, unprotected, optical access network configurations for rural settings. The research will also consider the potential of merging BPON and UPON strategies, aiming to harness the combined benefits of both architectures for a more versatile and cost-effective rural broadband deployment.

This comparative analysis is expected to keen insights into the scalability of BPON and UPON solutions, guiding network operators toward more informed infrastructure development decisions in rural settings. By analyzing multiple Gabriel graphs to evaluate total fiber length, splitter requirements, and infrastructure cost, this research aims to derive comprehensive guidelines for efficient fiber deployment in rural areas. These guidelines will contribute to internet access deployment strategies and help narrow the digital divide, showcasing UPON as an affordable and practical solution for rural broadband. By aligning with initiatives like the Broadband Programs in Germany and Bavaria, this research underscores the global effort to extend high-quality internet connectivity to underserved areas. [1] This analysis will thus empower network operators with the knowledge to select the most appropriate PON configuration for rural deployments, ensuring efficient, reliable, and affordable broadband access.

References:


[1] "State aid: Commission approves German scheme for very high capacity broadband networks in Bavaria." The European Sting, 29 Nov. 2019,
https://ec.europa.eu/commission/presscorner/detail/en/ip_19_6630.

Voraussetzungen

Knowledge of:

  • Python
  • Object Oriented Programming
  • GIT
  • Optical Networks
  • Linux

Kontakt

cristian.bermudez-serna@tum.de

Betreuer:

Cristian Bermudez Serna

Electrical Network and Optical Network Dependability

Stichworte:
Optical Access Network
Kurzbeschreibung:
The dependability that the electrical and optical networks have on each other is a critical factor in ensuring uninterrupted services to the large population of the landscape of urban infrastructure. This thesis aims to delve into the complexity of different protection schemes in optical networks and explore their interconnection with electrical networks through different kinds of failures. The motivation behind this thesis comes from the increasing reliance on digital and electrical services, making the importance of the robustness of the underlying infrastructure very critical. Additionally, the focus will be on urban areas due to their large number of population and complex infrastructural needs.

Beschreibung

The dependability that the electrical and optical networks have on each other is a critical factor in ensuring uninterrupted services to the large population of the landscape of urban infrastructure. This thesis aims to delve into the complexity of different protection schemes in optical networks and explore their interconnection with electrical networks through different kinds of failures. The motivation behind this thesis comes from the increasing reliance on digital and electrical services, making the importance of the robustness of the underlying infrastructure very critical. Additionally, the focus will be on urban areas due to their large number of population and complex infrastructural needs.

 

Protection schemes


Optical networks are backbone technologies that provide telecommunication services to urban areas and to safeguard these networks from failures and ensure continuity, different protection schemes are implemented.

  • Unprotected scheme: Basic configuration without any backup paths for the feeder fiber, leaving the network vulnerable to service disruptions.
  • Type A Protection (Feeder Fiber Protection): Incorporates a backup path for the feeder fiber's working path, enhancing reliability.
  • Type B Protection (Dual Parented): Each subscriber is connected to two Optical Line Terminals (OLTs) located in different geographical areas. This setup provides a secondary OLT as a backup, significantly reducing the risk of service interruption.
  • Type C Protection: Offers complete redundancy with two independent links extending to the subscriber's location, ensuring the highest level of network reliability.

The initial phase of this thesis involves mapping these protection schemes onto real-world urban layouts using OpenStreetMap data and Python scripting.

 

Failure Analysis and Impact Assessment

A critical aspect of network dependability is understanding how networks respond to failures and for this reason, this thesis implements different types of failures.
 

  • Node Failure: Focuses on the failure of Optical Line Terminals (OLTs) and Remote Nodes (RNs), excluding Optical Network Units (ONUs) since their failure impacts are isolated.
  • Edge Failure: Involves simulating failures of all network connections (edges) to assess the extent of impact on ONUs.
  • Disaster Failure: Examines the effects of large-scale disasters, using a defined centroid and radius, to determine the number of affected ONUs within the disaster zone.

 

To explain the impacts on network functionality and ONUs, for each failure type the thesis will present visualizations and statistical analysis like boxplots or histograms.
Interdependence with Electrical Networks Parallel to the exploration of optical networks, this thesis will study power network topologies, design constraints, and requirements necessary for integrating electrical network functionalities into the same urban layouts. Similar to the optical network, will simulate various power network failures and analyze their impacts on ONU connectivity. This approach aims to highlight and enhance the mutual dependability between electrical and optical networks, thereby increasing overall system robustness against failures.

All the work in this thesis is based on a combination of advanced scripting, data analysis libraries, and geospatial data sources to achieve its objectives. The primary tools and technologies used are Python, OpenStreetMap (OSM), and Python libraries. Some Python libraries are NetworkX which is used for creating and studying the structure of complex networks, and Pandas which is crucial for managing and analyzing the large datasets generated from OpenStreetMap and network simulations. Matplotlib and Seaborn to create static and interactive visualizations in Python.

 

Voraussetzungen

Knowledge of:

  • Python
  • Object Oriented Programming
  • GIT
  • Optical Networks
  • Linux

Kontakt

cristian.bermudez-serna@tum.de

Betreuer:

Cristian Bermudez Serna

Evaluation of Time Offset in 5G NR using USRPs

Kurzbeschreibung:
To evaluate the effect of Time Offset between base stations in 5G NR.

Beschreibung

The 3GPP standard has established a maximum time synchronization error, the indoor 5G network may be able to handle a higher value proposed by an earlier simulation. To validate and determine such a result, it is necessary to use real hardware to create a small network and test related aspects of it. Upper error limits serve a useful purpose in many network applications. The developer is able to establish the maximum permissible error by the network requirements to aid in the construction of networks.

Betreuer:

Yash Deshpande

RTT-guided Route Servers at IXPs

Beschreibung

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.

Betreuer:

Maximilian Stephan - Matthias Wichtlhuber (DE-CIX)

LFM Deep Dive: Understanding the Impact on 5G

Stichworte:
5G, AKA, LFM, Security

Beschreibung

Linkability of Failure Messages (LFM) is a security hole in the Authentication and Key Agreement (AKA) procedure.

The LFM flaw was first reported in 3G [2] and it has also been proven to work in 5G [1]. Compared to IMSI catchers, the use of the flaw for identifying nearby subscribers has two limitations: First, the attacker has to know the ID of a person of interest that they are looking for. Only these subscribers with known IDs can be detected, it is not possible to find the ID of a new subscriber without knowing / guessing it.

Second, LFM requires an attacker to probe every new device that connects to their fake base station for every ID that they are looking for. In addition to probing every new device, the attacker also needs to contact an authentic mobile network to obtain authentication requests for each person of interest.

Due to these limitations, the LFM flaw is less powerful than previously used IMSI catchers. The objective of this project is to examine the scalability and practicability of exploiting the flaw on a larger scale.

Betreuer:

Oliver Zeidler - Julian Sturm ()

Network Programmability-based Security Mechanisms in Optical Access Networks

Stichworte:
Network Programmability, Optical Access Networks, SDN, P4
Kurzbeschreibung:
The advent of Software-Defined Networking (SDN) has revolutionized the way networks are managed and secured. In the context of optical access networks, where performance and security are paramount, it is crucial to develop advanced mechanisms for safeguarding against threats like TCP-SYN flood attacks. This research proposal aims to investigate a novel approach to thwarting such attacks, leveraging SDN controllers and programmable switches, specifically in optical access networks.

Beschreibung

The advent of Software-Defined Networking (SDN) has revolutionized the way networks are managed and secured. In the context of optical access networks, where performance and security are paramount, it is crucial to develop advanced mechanisms for safeguarding against threats like TCP-SYN flood attacks. This research proposal aims to investigate a novel approach to thwarting such attacks, leveraging SDN controllers and programmable switches, specifically in optical access networks.

How can SDN controllers and programmable switches be employed to effectively detect and mitigate TCP-SYN flood attacks in optical access networks, utilizing authentication using a modified SYN-ACK exchange and actuating triggers, while maintaining network performance and reliability?

This research aims to contribute to the field of network security and SDN by providing a cutting-edge solution for mitigating TCP-SYN flood attacks in optical access networks. The expected outcomes include:

1. An innovative approach to SYN flood attack mitigation, leveraging SYN-ACK exchange and P4-based actuating triggers.

2. Insights into the performance and scalability of the proposed solution in optical access network scenarios.

3. A comprehensive evaluation of alternative SYN flood attack mitigation techniques, aiding network administrators in selecting the most appropriate method.

Voraussetzungen

  • Machine Learning
  • Python and P4 programming
  • Knowledge of Softrware-Defined Networking

 

Kontakt

cristian.bermudez-serna@tum.de

Betreuer:

Cristian Bermudez Serna

Exploration of Machine Learning for In-network Prediction and Classification

Stichworte:
Machine Learning, P4, SDN
Kurzbeschreibung:
A promising solution is to include a Machine Learning algorithm into the Data Plane. Specifically, Decision Trees (DT) and Random Forests (RF) can be used to do line-rate classification. Since Decision Trees do not require complex mathematical operations, they can be easily deployed into the programmable switches using P4 language. Either a per-packet or a per-flow approach, each with its advantages and its drawbacks, will automate the decision of the switch of how to handle the incoming traffic instead of always forwarding it first to the controller.

Beschreibung

Software defined networks (SDN) have made data traffic routing a lot more convenient. The functionality of the additional controller can be used e.g. for detecting network threats like DoS or also for load balancing by redirecting data traffic. The initial idea of SDNs is that each time a new packet enters the network the packet is first forwarded to the controller to be checked. The controller then decides on which route the packet shall be send inside the network or tells the network to drop the packet, for instance if it is a threat. Each of the switches then save this information in their match-action tables. However, this model cannot scale in large networks with thousands or even millions of different packets trafficking, since that would lead to an additional latency, if every single packet needs to be sent to the controller.

Therefore, a promising solution to improve the model is to include a Machine Learning algorithm into the process. Specifically, Decision Trees (DT) and Random Forests (RF) can be used to do this line-rate classification. Since Decision Trees do not require complex mathematical operations, they can be easily deployed into the programmable switches using P4 language. Either a per-packet or a per-flow approach, each with its advantages and its drawbacks, will automate the decision of the switch of how to handle the incoming traffic instead of always forwarding it first to the controller.

In this master thesis a realisation of a DT into the P4 switches will be tested. First a functioning DT based on a real data traffic dataset will be implemented. Both variations (per-packet/per-flow) will be taken into consideration. The second step will be to translate the algorithm into the P4 switches. Afterwards the prediction performance will be analysed. The final step will be to compare the ML approach to the non-ML approach and draw conclusions on the results.

Voraussetzungen

  • Machine Learning
  • Python and P4 programming
  • Knowledge of Softrware-Defined Networking

Kontakt

cristian.bermudez-serna@tum.de

Betreuer:

Cristian Bermudez Serna

Performance Evaluation of a 6G UAM Connected Sensor Fusion System

Beschreibung

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.

Betreuer:

Polina Kutsevol - Markus Klügel (Airbus)

Remote Monitoring of Correlated Sources Over Random Access Channels in IoT Systems

Beschreibung

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.

Betreuer:

Polina Kutsevol - Dr. Andrea Munari (DLR - Deutsches Zentrum für Luft- und Raumfahrt)

Analysis of UE-initiated Signaling Storms and Their Impact on 5G Network Security

Stichworte:
5G, Signaling Storm, UE initiated attacks, DDoS

Beschreibung

Signaling storm is a specific type of DDoS attack, which emerges from frequent small-scale signaling activities of a group of compromised UE. Typically, signaling messages are exchanged between UE and the network for establishing communication sessions and managing network resources. However, signaling attacks abuse regular procedures to generate high number of signaling messages within a short period. The generation of excessive signaling load increases the network congestion and consumes resources. In 5G, UEs must send a request to initiate themselves and establish the communication with the 5G core. These initial registration request messages contain UE related information about identity, location and capabilities. The recent research internship focused on signaling storms has revealed that an initial registration request flood can generate significant signaling load and stress the network core. In the scope of mentioned internship, a simulation environment was created using UERANSIM and open5GS to investigate the impact of repetitive initial registration requests from a botnet comprising hundreds of UEs on control plane resources. The master thesis involves a comprehensive research study based on this initial observation to identify other signaling attack scenarios initiated by UEs, that abuse regular UE signaling for registration processes, inter-slice handovers and mobility handovers. Furthermore, assessing the impact of these scenarios and exploring possible detection methodologies are crucial for the intended study.

Motivation: 5G networks are designed to be used for three types of connected services: Enhanced Mobile Broadband(eMBB), Ultra Reliable Low Latency Communications (URLLC) and Massive Machine Type Communications (mMTC). Higher throughput, reliable connections and low latency capabilities of 5G networks should meet uninterrupted and robust data exchange requirements of users. Both the industry and individual users heavily rely on seamless connectivity. However, numerous studies have shown that 5G networks are vulnerable to signaling threats and DDoS attacks, which are becoming more severe due to the growing number of mobile and IoT devices. Such attacks can increase latency and impact service availability. The majority of literature on this topic examines potential 5G threats including signal storms and their effect on users. Even some detection and prevention techniques have been proposed. Although these studies provide valuable information about signaling storms, it has not been particularly investigated how control plane resources can be exploited by flooding UE initiated and 5G protocol specific requests. The research gap regarding concrete statements to reproduce signaling attacks is the main motivation of this study.

Objectives and Research Question: This work will focus on UE initiated DDoS attacks targeting control plane resources of 5G networks and it will question if these attacks can have a severe impact on practical 5G test setup. Therefore, signaling procedures particularly the ones involving NAS and NGAP protocols, will be explored to identify scenarios for UE initiated signaling attacks. The characteristics of the identified scenarios will be derived by theoretical analysis. The remaining objectives are reproducing these scenarios conducting experiments with appropriate simulation tools, evaluating the impact of these attacks on the network and user experience and investigating detection solutions for signaling storms.

Challenges: The identified scenarios should be demonstrated and analyzed to study the research question, which poses two main challenges. Designing a simulation environment for realistic attack reproduction is elaborate, which requires determining the most suitable solution to simulate UE, gNB and 5GC among existing solutions. The simulation environment cannot completely replace the real 5G network and there will be some restrictions. Therefore, the second challenge is to design experiments in a way that allows the derivation of general statements about 5G security threats from observations made during the experiments

Contribution: This thesis will address the signaling attacks on the control plane of 5G networks by identifying concrete signaling scenarios to generate excessive packet floods, analyzing them, and demonstrating them to assess their impact on the network. The simulation environment will allow reproducing various attacks to derive characteristics of the attacks, which are required for detection by distinguishing between good and malicious communication patterns. Overall, this work will contribute to the improvement of network security.

Betreuer:

Oliver Zeidler, Maximilian Stephan - Tim Niehoff (IPOQUE)

Sustainable Edge Network Orchestration in 5G with Performance Guarantees

Stichworte:
5G, 5G Edge, UPF, Optimization, Heuristic

Beschreibung

With the advent of 5G cellular networks, more stringent types of traffic, pertaining to applications like augmented reality, virtual reality, and online gaming, are being served nowadays. However, this comes with an increased energy consumption on both the user’s and network side, challenging this way the sustainability of cellular networks. Furthermore, the in-network computing aspect exacerbates things even further in that direction. 

Hence, it is very important to provide end-to-end sustainability, i.e., minimize the energy consumption in the network while maintaining performance guarantees, such as the maximum latency each flow should experience. This can be done, for example, depending on the traffic load in the network, and in order to keep the energy usage at low levels, the operator can decide to shut off certain network components, like User Plane Functions (UPFs) or edge clouds, and reassign the tasks to other entities. 

In this thesis, the focus will be on the core network. The aforementioned decisions will come up as solutions to optimization problems. To that end, the student will formulate optimization problems and solve them either analytically or using an optimization solver (e.g., Gurobi). The other part would be conducting realistic simulations and showing the improvements with our approach. 

Voraussetzungen

- Basic understanding of 5G Core Networks and Mobile Edge Computing (MEC).

- Experience with mathematical formulation of optimization problems.

- Programming experience with Python and Gurobi.

Betreuer:

Endri Goshi, Fidan Mehmeti

The Analysis of Dual Data Gathering Strategy for Internet-of-Things Devices in Status Update Systems

Beschreibung

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.

Betreuer:

Polina Kutsevol - Dr. Andrea Munari (DLR - Deutsches Zentrum für Luft- und Raumfahrt)

Load Generation for Benchmarking Kubernetes Autoscaler

Stichworte:
Horizontal Pod Autoscaler (HPA), Kubernetes (K8s), Benchmarking

Beschreibung

Kubernetes (K8s) has become the de facto standard for orchestrating containerized applications. K8s is an open-source framework which among many features, provides automated scaling and management of services. 

Considering a microservice-based architecture, where each application is composed of multiple independent services (usually each service provides a single functionality), K8s' Horizontal Pod Autoscaler (HPA) can be leveraged to dynamically change the number of  instances (also known as Pods) based on workload and incoming request pattern.

The main focus of this project is to benchmark the HPA behavior of a Kubernetes cluster running a microservice-based application having multiple services chained together. That means, there is a dependency between multiple services, and by sending a request to a certain service, other services might be called once or multiple times.

This project aims to generate incoming request load patterns that lead to an increase in either the operational cost of the Kubernetes cluster or response time of the requests. This potentially helps to identify corner cases of the algorithm and/or weak spots of the system; hence called adversarial benchmarking.

The applications can be selected from commonly used benchmarks such as DeathStarBench*. The objective is to investigate on the dependencies between services and how different sequences of incoming request patterns can affect each service as well as the whole system.

* https://github.com/delimitrou/DeathStarBench/blob/master/hotelReservation/README.md

Betreuer:

Navidreza Asadi, Razvan-Mihai Ursu

End-to-End Scheduling in Large-Scale Deterministic Networks

Stichworte:
TSN, Scheduling, Industrial Networks
Kurzbeschreibung:
To evaluate APS in TSN Networks

Beschreibung

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.

Voraussetzungen

C++, Expeience with OMNET++, KNowledge of TSN.

Betreuer:

Yash Deshpande, Philip Diederich - Dr Siyu Tang (Huawei Technologies)

Forschungspraxis (Research Internships)

Extending Mininet to Support Basic IPX Functionality for a 5G Standalone (SA) Setup using Open5GS

Beschreibung

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.

Voraussetzungen

The primary objective of this internship is to extend Mininet’s capabilities to support basic IPX functionalities for a 5G SA setup. The research will focus on simulating the roaming scenario between a Visited Public Land Mobile Network (VPLMN) and a Home Public Land Mobile Network (HPLMN) using Open5GS.

Implementation objectives include (all would be nice, but if time runs out, then also a couple of them shall suffice):
• setting up Mininet and configuring it for this use-case
• adding support for MPLS
• adding support for HTTP Connect
• adding support for PRINS
• adding support for GTP-U
• adding support for IPUPS
• integrating the Mininet IPX into the 5g Roaming Testbed

Betreuer:

Oliver Zeidler

Implementation of a Containerized Setup for the Semiautonomous Telerobotic Examination Suite

Beschreibung

Containerizing the ROS2 components according to the MAF concept.

Betreuer:

Nicolai Kröger - Sven Kolb (MITI)

Investigation and Capability Assessment of LiFi Standards

Beschreibung

Comparing current light communication standards, specifically ITU G.9991,
IEEE 802.15.13, and IEEE 802.11bb

Betreuer:

Hansini Vijayaraghavan - (aeroLiFi GmbH)

Temporal Graph Learning for IP-level NTMA

Stichworte:
tgl, gnn, ntma
Kurzbeschreibung:
Evaluation of how current tools for temporal graph learning (TGL) can be used in IP-level network traffic monitoring and analysis.

Beschreibung

Analyzing traffic in today's communication networks becomes more and more complex due to the increasing heterogeneity of networked devices and general rising traffic volumes. 
In this context, data-driven methods can facilitate a deep understanding of the inherent dynamics needed to operate such networks efficiently.

Because network-related data is often naturally represented in graph form, this Internship specifically seeks to evaluate how methods from the Pytorch library for temporal graph learning, "PyTorch Geometric Temporal," can be applied to IP-to-IP level data.  

Goal is to among others to predict:

  • IP-node activity over time 
  • IP-to-IP level communications (e.g. number of packets) over time

Steps:

  1. Set up a working ML pipeline.
  2. Fine-tune models / try different models.
  3. Identify promising directions and limitations
  4. Conclude what needs to be done/tried in the future.

Voraussetzungen

  • knowledge in python 
  • basic knowledge in ML
  • basic knowledge about  IP networks 

Betreuer:

Maximilian Stephan, Kaan Aykurt

Design and Evaluation of Detection Methods for an Experimental Molecular Communication Platform

Beschreibung

Molecular communication (MC) is a novel communication paradigm envisioned to enable revolutionary future medical and biological use cases such as in-body networks for the diagnosis and treatment of diseases. MC is based on the transport of molecules for information exchange and represents a very energy-efficient and bio-compatible communication mechanism on the centimeter to nanometer scale. The communication nodes can be very small as they will be based on artificial cells or other types of tiny nano-machines.

In order to realize complex applications, such as targeted drug delivery or the detection and localization of infections and tumors, nano-machines must cooperate and communicate. The specific properties and mechanisms in biological environments and at very small scales lead to several challenges:

  • Novel channel models and conditions based on diffusion and flow of molecules.
  • Extremely slow speeds compared to electromagnetic waves.
  • Highly stochastic behavior of the molecules.
  • Low capability of future nano-machines, not able to conduct complex computations or sophisticated algorithms.

Therefore, research on MC networks is crucial to enable a future internet of bio-nano things (IoBNT) integrating classical and molecular networks.

 

In this internship, the student will work with experimental data from an MC testbed to implement, evaluate, and improve detection algorithms. The considered algorithms range from simple to complex, including symbol-by-symbol detection, sequence detection, matched filters, etc. The goal is to identify the strengths and weaknesses of various algorithms with respect to the characteristics of the MC signal at the receiver.

Kontakt

alexander.wietfeld@tum.de

Betreuer:

Alexander Wietfeld

Topology Upgrade for Optimal and Reliable Multi-Period Network Planning

Beschreibung

Optical networks are crucial for digital communications, handling massive data transport over long distances with wavelength division multiplexing (WDM) in the C-band. However, growing traffic demands may surpass conventional WDM capacities, prompting the exploration of ultra-wideband (UWB) and spatial division multiplexing (SDM) solutions. SDM increases throughput by utilizing different spatial domains, while UWB increases the available spectrum by taking advantage of transmission over multiple bands. Despite hesitancy due to cost, network operators recognize the need for optimal topology upgrades to meet evolving traffic demands, especially when reliability is taken into account. On top of the SDM and UWB upgrades on the existing topology, this also includes installing new links that do not exist in the original topology.

In this thesis, the goal is to optimally add links to existing core network topologies using the aforementioned schemes (SDM and UWB), according to increasing traffic demands, towards minimum cost, and considering reliability constraints, such as dedicated 1+1 protection for the demands.

Voraussetzungen

  • Basic knowledge of optical networks and network reliability.
  • Experience in Python.
  • Experience with formulating and solving Integer Linear Programming (ILP) problems.

Kontakt

maria.samonaki@tum.de

Betreuer:

Maria Samonaki

Detailed Requirement Analysis for the Reliability and Availability of Medical Network Communication

Beschreibung

 

6G soll als neuer und zukünftiger Mobilfunkstandard den Menschen in den Fokus rücken. Neben sehr geringen Latenzen und extrem großen Datenübertragungsraten wird das Netzwerk zuverlässiger, sicherer und dynamischer. Diese Eigenschaften sind besonders in der Medizin und der Medizingerätetechnik gefragt, um intelligente Datenübertragung zwischen Geräten und Menschen zu ermöglichen. Im Rahmen des Verbundprojektes „6G-life“ sollen zwei medizinische Demonstratoren entwickelt werden, die diese Netzwerkeigenschaften untersuchen. Ein Demonstrator ist ein robotisches Telediagnostiksystem zur Remote Untersuchung von Patienten. Ein zweiter Demonstrator beschäftigt sich mit der raumadaptiven Erfassung von Vitalparametern.

Ziel der Forschungspraxis ist die Ermittlung von medizintechnischen Anforderungen an die Netzwerkkommunikation hinsichtlich der Ausfallsicherheit. Dies beinhaltet eine Recherche gängiger Normen und Richtlinien, die bei der medizinischen Datenübertragung berücksichtigt werden müssen, sowie Maßnahmen, die zur Sicherstellung zuverlässiger Kommunikation getroffen werden können. Darüber hinaus sind Interviews mit Medizinern wünschenswert, um die Nutzerseite zu berücksichtigen.

 

Im Rahmen der Arbeit sollen folgende Punkte behandelt werden:

  • Recherche zu gängigen Richtlinien und Mechanismen, die in der medizintechnischen Netzwerkkommunikation zur Ausfallsicherheit eingesetzt werden.
  • Interviews mit Klinikpersonal
  • Evtl. Messung mit den vorhandenen Testbeds

 

Diese FP wird in Kooperation mit unseren Partnern der MITI Gruppe am Krankenhaus "Rechts der Isar" durchgeführt.

 

Voraussetzungen

  • Motivation
  • Interesse an Medizintechnik
  • Deutsch (zwingend erforderlich zwecks der Interviews)
  • Grundlegende Kenntnisse über Netzwerkkonzepte

 

Betreuer:

Nicolai Kröger - Franziska Jurosch (MITI)

Evaluation of Time Synchronization in NR UE-UE Interference Scenarios

Kurzbeschreibung:
Evaluate UE-UE interference in case of time offset in 5G

Beschreibung

This research internship aims to assess the impact of time synchronization discrepancies between base stations located in different cells. When time offsets occur, transmissions from one cell may reach user equipment (UEs) in neighboring cells at unintended times, resulting in interference and potential performance degradation.

This research internship will set up a MATLAB simulation to evaluate this scenario.

Voraussetzungen

  1. Understanding of 5G systems.
  2. Design of Experiments.
  3. Experience with MATLAB.

Betreuer:

Yash Deshpande

Performance Evaluation of Serverless Frameworks

Stichworte:
Serverless, Function as a Service, Machine Learning, Distributed ML

Beschreibung

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.

Betreuer:

Navidreza Asadi

Analyzing the Efficiency and Accuracy of Reinforcement Learning for Finding Optimal Paths

Stichworte:
Quantum key distribution, reinforcement learning

Beschreibung

The research internship aims to implement a reinforcement learning (RL) algorithm using Python to optimize routing agents in QKD networks. The literature showed different proof of concepts from other applications, and the research internship's objective is to adapt the best-suited one to the characteristics of QKD. 

Voraussetzungen

- Background in AI/ML

- Experienced in Python

- Experienced in Statistics

Kontakt

Mario Wenning

mario.wenning@tum.de

Betreuer:

Mario Wenning

Evaluation of Time Synchronization in NR BS-BS Interference Scenarios

Kurzbeschreibung:
To evaluate time offset in agressor victim simulations in 5G NR

Beschreibung

The research will utilize the 5G-NR functions available in Matlab for a two-base station scenario, each having multiple UEs connected in both cells. The throughput and block error rate of a UE at the edge of the cell will be evaluated for multiple simulations for different values of delayed transmission in the interfering base station. The study will also incorporate the other BS parameters, such as BS transmit power and the distance between the two BSs, and analyze their influence on the results obtained.

Betreuer:

Yash Deshpande

A Study on Learning-Based Horizontal Autoscaling on Kubernetes

Stichworte:
Autoscaling, Kubernetes, Edge Computing

Beschreibung

 The rapid growth of edge computing has introduced new challenges in managing and scaling workloads in distributed environments to maintain stable service performance while saving resources. To address this, this research internship aims to explore the feasibility and implications of extending the AWARE framework (Qiu et al., 2023) [1], which has been developed by as an automated workload autoscaling solution for production cloud systems, to edge environments. 

 

 AWARE utilizes tools such as reinforcement learning, meta-learning, and bootstrapping when scaling out workloads in the horizontal dimension by increasing the number of deployment instances and scaling up in the vertical dimension by increasing the allocated resources of a deployment instance. We will employ edge environment infrastructures with limited resources that run a lightweight distribution of the Kubernetes (K8s) container orchestration tool, and the goal is to gain insights into the performance, adaptability, and limitations of this approach.

Betreuer:

Navidreza Asadi

Development and Evaluation of an Intelligent Wireless Resource Management for 5G/6G Downlink Channel

Beschreibung

In this work, we will evaluate several additional techniques in 5G/6G toward reliability enhancements focusing on the Radio Access Network (RAN). The student is expected to first understand and evaluate the concept via simulations over MATLAB. Then, the techniques will be implemented in OpenAirInterface (OAI) [1] platform and we will evaluate the enhancements over our practical 5G testbed setup.

The initial setup will include a mobile robot, 5G Stand-alone communication, and a multi-access edge computing (MEC) system running a machine learning algorithm.

The expected outcome is to have improvements to the RAN of OAI including but not limited to wireless channel estimation and equalization, downlink reliability. More details will be provided after the first meeting.

[1] N.Nikaein, M.K. Marina, S. Manickam, A.Dawson, R. Knopp and C.Bonnet,
“OpenAirInterface: A flexible platform for 5G research,” ACM SIGCOMM Computer
Communication Review, vol. 44, no. 5, 2014.

Voraussetzungen

- Good C/C++ experience

- Good Matlab knowledge

 - Medium knowledge on OFDM and Wireless Channel Estimation

- Good Python knowledge is a plus

- Machine Learning understanding is a plus

Kontakt

serkut.ayvasik@tum.de

Betreuer:

ILP-based network planning for the future railway communications

Stichworte:
Network Planning, On-Train Data Communications. Integer Linear Programming
Kurzbeschreibung:
Exploration of mechanisms for handling data communications under the influence of mobility in the German long distance railway system.

Beschreibung

This work focuses on the exploration of networks enabling train control and on-board data communications under mobility scenarios. Today, low bandwidth networks such as GSM, providing less than 200 Kbps are being used to transmit train control information. Moreover, despite trains may use multiple on-board technologies to provide users with an internet connection (e.g., repeaters, access points), they fail in their attempt as these connections are characterized by having low throughput (less than 2 Mbps) and frequent service interruptions.

This work aims at the development of a network planning solution enabling future applications in train mobility scenarios such as: Automatic Train Operation (ATO) [1,2], leveraging cloud technologies and meeting bandwidth requirements of data-hungry end-users' applications. Here, special attention will be given to the migration of communications services triggered by trains mobility patterns. It is expected of the student to find solutions to the following questions:

  • When to trigger service migrations?

  • Where to migrate services? (i.e., to which data center)

  • How to handle this process? (So that the user does not perceive any interruption)

 Given:

  • Trains mobility patterns

  • Service requirements in terms of bandwidth and delay

  • Network topology

  • Data center locations

 
The results from this work can be useful to get an insight on requirements for Smart Transportation Systems, that may in turn be useful for cementing the basis of other scenarios such as: Autonomous Driving and Tele-Operated Driving.

 [1] Digitale Schiene Deutschland. Last visit on 13.12.2021 https://digitale-schiene-deutschland.de/FRMCS-5G-Datenkommunikation

[2] 5G-Rail FRMCS. Last visit on 13.12.2021 https://5grail.eu/frmcs/

Voraussetzungen

Basic knowledge in:

  • Integer Linear Programming (ILP), heuristics or Machine Learning (ML).

  • Python

Please send your CV and transcript of records.

 

Kontakt

Betreuer:

Cristian Bermudez Serna

Machine-learning-based network planning for the future railway communications

Stichworte:
Network Planning, On-Train Data Communications. Machine Learning
Kurzbeschreibung:
Exploration of mechanisms for handling data communications under the influence of mobility in the German long distance railway system.

Beschreibung

This work focuses on the exploration of networks enabling train control and on-board data communications under mobility scenarios. Today, low bandwidth networks such as GSM, providing less than 200 Kbps are being used to transmit train control information. Moreover, despite trains may use multiple on-board technologies to provide users with an internet connection (e.g., repeaters, access points), they fail in their attempt as these connections are characterized by having low throughput (less than 2 Mbps) and frequent service interruptions.

This work aims at the development of a network planning solution enabling future applications in train mobility scenarios such as: Automatic Train Operation (ATO) [1,2], leveraging cloud technologies and meeting bandwidth requirements of data-hungry end-users' applications. Here, special attention will be given to the migration of communications services triggered by trains mobility patterns. It is expected of the student to find solutions to the following questions:

  • When to trigger service migrations?

  • Where to migrate services? (i.e., to which data center)

  • How to handle this process? (So that the user does not perceive any interruption)

 Given:

  • Trains mobility patterns

  • Service requirements in terms of bandwidth and delay

  • Network topology

  • Data center locations

 
The results from this work can be useful to get an insight on requirements for Smart Transportation Systems, that may in turn be useful for cementing the basis of other scenarios such as: Autonomous Driving and Tele-Operated Driving.

 [1] Digitale Schiene Deutschland. Last visit on 13.12.2021 https://digitale-schiene-deutschland.de/FRMCS-5G-Datenkommunikation

[2] 5G-Rail FRMCS. Last visit on 13.12.2021 https://5grail.eu/frmcs/

Voraussetzungen

Basic knowledge in:

  • Integer Linear Programming (ILP), heuristics or Machine Learning (ML).

  • Python

Please send your CV and transcript of records.

 

Kontakt

Betreuer:

Cristian Bermudez Serna

Ingenieurpraxis

Praktikantin Planung, Steuerungstechnik und produktionsnahe IT

Beschreibung

...

Betreuer:

Data Analysis and Prediction of Optical Network Performance on Open Source Data

Beschreibung

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.

Kontakt

jasper.mueller@adtran.com

Betreuer:

Jasper Konstantin Müller - Jasper Müller (Adtran Networks SE)

Studentische Hilfskräfte

Working Student for Implementing and Maintaining a 5G Roaming Testbed

Stichworte:
5G, Roaming, Core Network, Network Functions

Beschreibung

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

Voraussetzungen

• Motivation and team spirit

• Basic understanding of 5G networks advantageous; especially of the 5G core network

    – interest and motivation to learn the system are sufficient

• Programming knowledge in C useful (for Open5GS)

• Interest in Roaming functionalities

• Interest in security

Kontakt

Oliver Zeidler (oliver.zeidler@tum.de)

Julian Sturm (julian.sturm@tum.de)

Betreuer:

Oliver Zeidler

Working Student for the Medical Testbed

Beschreibung

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.

 

Voraussetzungen

Most important:

  • Motivation and willingness to learn unknown things.
  • Ability to work with various partners (teamwork ability).

 

Of advantage:

  • C/C++ and knowledge about how other programming languages work (Python, etc.)
  • Knowledge about communication networks (exspecially the RAN), 5G concepts, the P4 language, SDN, Linux.
  • Initiative to bring in own ideas and solutions.

Please note: It is not necessary to know about every topic aforementioned, much more it is important to be willing to read oneself in.

 

Betreuer:

Nicolai Kröger