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Technical University of Munich

Advanced Seminar Embedded Systems and Internet of Things

Application Process

 

Due to the high interest in our seminar topics we use an application process to assign the topics.

If you are interested in one of the topics below, please send your application together with your CV and your transcript of records to seminar.esi.ei(at)tum.de. Express your interest and explain why you want to have that specific topic and why you think that you are most suitable for the topic. This allows us to choose the most suitable candidate for the desired topic to maximize the seminar's learning outcome and to avoid dropouts.

Additionally, you can indicate a second topic that you would like to take, such that we can still find a topic for you if your primary choice is not available.

Deadline: We encourage you to apply until the 11.10.2022. Afterwards we will assign the topics and notify all applicants. After this date, we will answer to requests within 3 days, assuming that there is enough motivation for the given topic. Once you are given the topic, we will ask for your confirmation.

Note: We do not assign topics on a first-come-first-served basis. Even though we appreciate your interest if you have asked or applied early for a topic we can not guarantee that you get a seat. Generally we have 3-4 applicants per topic. Please think carefully if you are able to do the work required as we have to reject other students. Generally, email clients remember the people you have communicated with.

 

Kick-off meeting

This semester the seminar will be conducted in physical mode. If physical mode is not possible then it will be conducted as an online class. You will have weekly meetings with your supervisor via Zoom or on campus while lecture materials and videos will be available on Moodle.

The kick-off meeting will be on the 19th of October at 9:45 on Campus. We ask all selected participants who have accepted a topic to be present in the kick-off meeting. Please notify us in case you can not make it to the meeting, otherwise we will assume that you are no longer interested and give your place to another applicant.

 

Topics

This semester we offer the following 10 topics for the advanced seminar "Embedded Systems and Internet of Things":

  1. FPGA-Based TSN Traffic Scheduling and Shaping
  2. TSN requirement in Vehicular Communication
  3. A state-of-the-art analysis of frameworks implementing ZK-SNARK systems
  4. Role Assignment in "You Only Speak Once" style protocols
  5. Temporary Private 5G networks
  6. 5G Non-Terrestrial Networks Use Cases
  7. 5G URLLC for Private Networks
  8. Machine-readable Descriptions of the 3D scenes and Simulations
  9. Towards Predictive Maintenance of a Hyperloop’s Magnetic Suspension System using Machine Learning Techniques
  10. Application of knowledge graphs for digital twins in Industry 4.0

You will find the description of the topics below. Furthermore, we gave you a few references for each topic as a starting point for your research. Your task for each topic will be to read and analyze related literature, get an overview of the current state-of-the-art and summarize your findings in a paper-style report. Afterwards you will present your findings in a "mini-conference" in front of your fellow students.

During the seminar you will also learn through the lecture how to conduct the research, how to write a scientific paper and how to present your work.

 

1. FPGA-Based TSN Traffic Scheduling and Shaping

Time-sensitive networking (TSN) is a promising technology for industrial automation and autonomous driving. Most of the performance analysis of TSN shapers are based on simulation and quantitative approaches. The end result of TSN is the final implementation in the hardware and for the complexity and cost of the implementation it is important to study the hardware aspect of TSN shapers. In this topic, the students have to evaluate and compare the Field Programmable Gate Arrays (FPGA) implementation of different TSN scheduling techniques.

Your task for this topic is:

1) Propose FPGA based implementations of different TSN scheduling.

2) Investigate current state-of-the-art FPGA-based prototyping for different TSN components.

3) Investigate the complexity, cost and CLBs (configurable logic blocks) for different TSN shapers.

References:

Supervisor: Rubi Debnath

Assigned

 

2. TSN requirement in Vehicular Communication

Time-sensitive networking (TSN) is a set of standards which enables deterministic transmission on standard Ethernet. TSN is a potential candidate for vehicular communication and autonomous driving. 

In this topic, the student has to look for the current vehicular topologies and requirements which is used for validation and performance analysis of TSN. 

Your task for this topic is:

  1. Investigate different vehicular topologies published in current state-of-the-art.
  2. Investigate how TSN performs in vehicular networks.
  3. Investigate the requirements of vehicular networks in terms of latency and jitter.

References:

Supervisor: Rubi Debnath

Assigned

 

3. A state-of-the-art analysis of frameworks implementing ZK-SNARK systems

Description: Recently, frameworks that implement different ZK-SNARK systems have emerged in multiple languages. Most frameworks come with support for the Groth16 or Plonk backends and build different language specific frontends to facilitate arithmetic circuit development for users. On top, some frameworks feature automatic smart contract generation to enable on-chain proof verification, and others bring ZKP capabilities to browser environments. To bring new privacy-preserving applications to IoT devices, the task of the student is to create a state-of-the-art overview over existing ZK-SNARK frameworks and their different features in order to asses which ZK-SNARK framework work best in resource-constraint environments.

References:

Supervisor: Jan Lauinger

Assigned

 

4. Role Assignment in "You Only Speak Once" style protocols

Blockchain Consensus algorithms have an interesting, unique property. Any member in the committee can "win" the right to propose a new block by solving a local "lottery", which involves randomness to determine the respective block proposer. Once the proposer has been determined, it sends a SINGLE message and otherwise keeps silent. Recent work coined this type of protocols of this kind as "You Only Speak Once" [1]. This type of protocol is especially interesting in orthogonal applications beyond blockchains, where comittee members keep track of a specific "secret" (such as secret input to a private computation).
A problem in this setting is that committee members who are elected to hold the secret cannot be known in advance, i.e. the initial holder of the secret needs to send its message to an unknown receiver (This is also true in the case of multiple rounds, where committees hand over secrets to the next committee)[2]. The problem of electing this subset of the committee is known as the "Role Assignment" problem and brought forward novel solutions in most recent works on YOSO style protocols[1,2].
In this topic, it is your task to

  1. Investigate current solutions for role assignment problems in YOSO style protocols.
  2. And conduct an in-depth review of their motivation and specific pitfalls that are yet unsolved.

You can find a high level introduction to this problem in [3].
 

References:

Supervisor: Jens Ernstberger

Assigned

 

5. Temporary Private 5G networks

A private fifth generation (5G) network is a dedicated 5G network with enhanced communication characteristics, unified connectivity, optimized services, and customized security within a specific area. Moreover, 5G has tremendous flexibility to adjust different use cases. For temporary organizations such as festivals and sporting events, the need for customizable communication networks are crucial.

In this seminar, you will identify the state-of-the-art papers on temporary 5G private networks and subsequently perform a survey.

Rapid Network Planning of Temporary Private 5G Networks with Unsupervised Machine Learning

Private 5G Networks: Concepts, Architectures, and Research Landscape

References:

Supervisor: Mustafa Selman Akinci

Assigned

 

6. 5G Non-Terrestrial Networks Use Cases

In 3GPP Release 17, non-terrestrial networks (NTNs) aim to bring 5G New Radio (NR) communications to unserved and isolated areas. Non-Terrestrial Networks (NTN) are able to satisfy requests of anywhere and anytime connection by offering wide-area coverage and ensuring service availability, continuity, and scalability. In this seminar, you will identify the state-of-the-art papers on 5G NTNs use cases and subsequently perform a survey.

Non-Terrestrial Networks in 5G &Beyond: A Survey

5G from Space: An Overview of 3GPP Non-Terrestrial Networks

5G New Radio Mobility Performance in LEO-based Non-Terrestrial Networks

 

References:

Supervisor: Mustafa Selman Akinci

Assigned

 

7. 5G URLLC for Private Networks

5G NR introduced Ultra Reliable and Low Latency Communication (urLLC) enabling real-time capabilities to different verticals, addressing use cases in factory automation, the transport industry, and electrical power distribution, etc.. Moreover, URLLC should co-exist with incumbent and emerging industrial Ethernet systems such as Time Sensitive Networking (TSN) in a heterogenous networking architecture. In this seminar, you will identify the state-of-the-art papers on 5G URLLC for private networks, supporting industrial automation and coexistence with TSN. Subsequently you will perform a survey.

5G URLLC: Evolution of High-Performance Wireless Networking for Industrial Automation

Customized 5G and Beyond Private Networks with Integrated URLLC, eMBB, mMTC, and Positioning for Industrial Verticals

URLLC and eMBB in 5G Industrial IoT: A Survey

References:

Supervisor: Mustafa Selman Akinci

Assigned

 

8. Machine-readable Descriptions of the 3D scenes and Simulations

Developing applications in for the Industrial Internet of Things (IIoT) is complex and costly, because such systems rely on an interplay between cyber systems and physical systems.

Therefore, IIoT development benefits greatly from a simulation-driven approach to design, development and testing, as it allows for the verification of the system’s behavior without the need to deployment, minimizing costs.

Furthermore, Digital Twins (DT) that shadow the physical devices could give insights about the device’s state and behavior during runtime.

To generate such simulations, it is important not to only describe the devices in that system, but also the environment in which the simulation is running.

In this seminar, you will identify different, machine-readable descriptions of 3D scenes and simulation environments and compare them with each other in the form of a survey.

 

References:

Supervisor: Fady Salama

Assigned

9. Towards Predictive Maintenance of a Hyperloop’s Magnetic Suspension System using Machine Learning Techniques

Hyperloop systems will use magnetic levitation systems to reduce drag and therefore achieve extremely high velocities. Since mechanical backup solutions are difficult to operate at such high velocities, Hyperloop systems rely on their electromechanical system for operation.
To detect and classify anomalies, like wear and tear, machine learning algorithms can be used. Since magnetic suspension requires a variety of sensors like acceleration sensors, distance sensors, and magnetic sensors which could be used to feed the machine learning algorithms.

Your task for this topic are:

  • Identification of suitable neural network topologies to achieve classification of time series sensor data
  • Comparison of these neural network topologies regarding their applicability in magnetic levitation systems
    References:

References:

Supervisor: Julian Demicoli

Assigned

10. Application of knowledge graphs for digital twins in Industry 4.0

The recent trend towards mass configurable items demands extremely high flexibility of production plants. However, self-adaptation to changing environments is difficult to achieve in state of the art systems. Digital twins, which form semantic copies of certain components of a production plant can support self-adaptation, since changing configurations can be simulated in the cloud before they are applied. This however requires the digital twin to cope with complex data interdependencies which are difficult to describe using normal databases. Knowledge graphs present a solution for this since they can model heterogenous data in a flexible manner.

References:

Supervisor: Julian Demicoli

Assigned

 

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