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@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 01.10.2021. 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 may be conducted in physical mode depending on the situation. 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 20th of October at 9:45 on Zoom or 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 8 topics for the advanced seminar "Embedded Systems and Internet of Things":

  1. Security-Aware Scheduling for Real-Time Systems
  2. Smart contract identity and key management and standards
  3. Towards Ledger Swap Protocols for Portable On-Ledger Identifier
  4. Reinforcement Learning based approaches for network configuration
  5. Machine Learning in Time Sensitive Network
  6. Resilience for IoT
  7. Scenario-based Specifications
  8. Sybil Resistance for Decentralized Identity Systems

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. Security-Aware Scheduling for Real-Time Systems

Most of the safety-critical systems (e.g., smart vehicles, avionics, smart grid, etc.)  are defined as hard real-time systems. These systems have a strict latency constraint that must be met. At the same time, these systems were and are still vulnerable to many security attacks. Introducing security measures for such systems may tamper with their temporal constraints and schedulability. Having security-aware scheduling algorithms can help to find a trade-off between the desired level of security and the service guarantee. Your task is to review  and compare some of the existing security-aware scheduling algorithms.

References:

Supervisor: Mohammad Hamad

Assigned

 

2. Smart contract identity and key management and standards

Smart contract based identity management provides blockchain features of immutable transaction history and availability. In addition, future on-chain identity management could make managed devices (e.g. IoT devices) independent of trusted third parties (e.g. identity service providers (IdPs) in federated identity management). Your task is to perform a literature review on latest smart contract concepts for on-chain identity management. In addition, your task is to investigate existing smart contract standards that deal with id/key management (e.g. ERC 725, ERC 734, ERC 721) to verify applicability in existing identity smart contract solutions. When comparing smart contract identity management solutions, your task is to highlight contract support of privacy preserving technologies, certification and credential capabilities, and key/owner management techniques (e.g. key rotation support, ownership transfer, delegation, revocation, etc.).

References:

Supervisor: Jan Lauinger

Assigned

 

3. Towards Ledger Swap Protocols for Portable On-Ledger Identifier

Due to attractive blockchain properties, smart contract based identity management gains attention if privacy guarantees of regular identity management protocols apply equally. One feature of traditional identity management systems is portability. To achieve cross-ledger identity portability, token swap protocols serve as a promising technique. Your task is perform a literature review on state-of-the-art cross-ledger swap protocols. Common features and requirements of existing swap protocols should be identified and contrasted with regard to performance, complexity, finality, and security.

References:

Supervisor: Jan Lauinger

Assigned

 

4. Reinforcement learning based approaches for network configuration

Network configuration allows to set up a network to communicate efficiently while reducing downtime. There are many computationally difficult problems for which many ILP, SMT, and heuristic algorithms have been proposed over time. But the challenge still remains to provide a fast and optimized solution for the large-scale industrial network.
Reinforcement learning is gaining widespread popularity over the recent years to solve different network configuration problems such as wireless resource allocation, routing, and scheduling problems. 
 
In this work, the student has to perform a survey and a comparison of the different state-of-the-art network configuration techniques using RL.

References:

Supervisor: Rubi Debnath

Assigned

 

5. Machine learning in Time Sensitive Network 

In a large-scale industrial network, the configuration and management of resources become very challenging. With the increase in the size of the network, the complexity also starts increasing exponentially. Once a Time-Sensitive Network is configured, it is challenging to re-configure it because of the high overhead to generate the gate control list for the Time-Triggered traffic. However, in any real-time industrial application, dynamic reconfiguration is needed to meet the changing requirements.  Machine learning provides a solution in addressing the challenges of resource management and configuration problem in large-scale industrial TSN networks.
 
This seminar aims to identify the state-of-the-art papers concerning the machine learning use case in the Time-Sensitive Networking domain and subsequently to perform a survey.

References:

Supervisor: Rubi Debnath

Assigned

 

6. Resilience for IoT

Resilience extends reliability for low-probability but high impact scenarios with recoverability. This characteristic is crucial for future IoT systems. For this topic, you will investigate the state of the art in resilience strategies and scenarios with respect to IoT.

References:

Supervisor: Laurin Prenzel

Assigned

 

7. Scenario-based Specifications

Scenarios are partial descriptions that contribute to an overall system description that may be used uncover design flaws in a system design. In this topic, you will compare the recent works on scenario-based specifications, e.g. with respect to their purpose, languages, and tools used.

References:

Supervisor: Laurin Prenzel

Assigned

 

8. Sybil Resistance for Decentralized Identity Systems

Decentralized Identity Management Systems as defined in the Decentralized Identifier and Verifiable Credentials standards [1,2] do not consider a significant problem that arises with digital identity management: Sybil Resistance. In the context of decentralized identity management, sybil resistance describes that  each user has a unique per-user identity and there is no user with two identities in the system. Recent work solves this problem by introducing frequent pseudonym parties [3] and credential deduplication approaches [4].

Your task for this topic is threefold:

  • Propose a definition for Sybil Resistance in Decentralized Identity Management
  • Investigate current approaches to Sybil Resistance (e.g. Proof of Personhood [3], Oracle approaches [4,5,6]) and compare them to each other with regard to privacy, security and performance.
  • Summarize application areas that demand for high sybil resistance (e.g. Voting) and to what extent they could be adressed through the respective approaches.

References:

Supervisor: Jens Ernstberger

Assigned