Advanced Distributed Systems - Interactive curriculae of TU Ilmenau
The interactive curriculae provide information on the degree programmes offered by the TU Ilmenau.
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You can find all details on planned lectures and classes in the course catalogue.
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| module properties Advanced Distributed Systems in degree program Master Data Science 2026 | |
|---|---|
| module number | 201197 |
| examination number | 2200875 |
| department | Department of Computer Science and Automation |
| ID of group | 2255 (Distributed Systems and Operating Systems) |
| module leader | Prof. Dr. Boris Koldehofe |
| term | winter term only |
| language | Englisch |
| credit points | 5 |
| on-campus program (h) | 45 |
| self-study (h) | 105 |
| obligation | elective module |
| exam | oral examination performance, 30 minutes |
| details of the certificate | |
| link to Moodle course | https://moodle.tu-ilmenau.de/course/view.php?id=3845 |
| teacher | Prof. Dr. Boris Koldehofe |
| signup details for alternative examinations | |
| maximum number of participants | |
| previous knowledge and experience | Pre-knowledge on fundamental aspects of computer science obtained for instance in a BSc program, in particular data structures and algorithms, basic concepts of programming languages, basic knowledge on computer networks, computer architecture or distributed and operating system principles. |
| learning outcome | At the end of the course, students can reproduce and explain concepts for dealing with dynamic and large-scale distributed systems. Students show a deep understanding of system concepts to ensure performance, robustness, and security of distributed applications. Students can explain the properties of specific concepts for autoscaling and securing distributed applications and demonstrate, analyze, and prove their behavior. Students are able to interpret and use different models and abstractions of advanced distributed systems and select appropriate mechanisms for dealing with highly heterogenous components from the continuum of resources comprising IoT devices, edge resources, cloud resources, and network components. The student can compare the suitability of algorithms and mechanisms for specific advanced distributed systems applications, reason about their limitations, and can relate the findings to particular use cases, e.g., the Internet of Things and scalable data analysis. |
| content | Nowadays, distributed systems are highly dynamic and often integrate many heterogeneous resources for computing communication and storage over a continuum of cloud data centers, edge data centers, user devices, sensors, and network components. In this course, students will study the principles behind current distributed technologies and modern architectures that support building highly scalable and robust distributed applications. The goal of the course is to develop an understanding of the principles behind advanced distributed systems technologies and programming concepts to build scalable, robust, and secure distributed systems applications. In particular, the lecture will cover the following topics: 1) Modern technologies and architectural concepts of distributed systems covering principles behind cloud, edge, fog, serverless and in-network computing 2) Systematic study of autoscaling concepts for distributed systems 3) Accelerating the performance of distributed systems with hardware accelerators and new system concepts, e.g., P4, DPDK, and RDMA 4) Advanced distributed programming concepts supporting scalable and robust distributed systems, e.g., asynchronous communication, distributed ledgers, distributed machine learning 5) Advanced security and privacy mechanisms, e.g., differential privacy, attribute-based encryption, distributed authentication and authorization architectures and federated learning |
| media of instruction and technical requirements for education and examination in case of online participation | Slides Lecture Recording Exercise Assignments & Solutions Quizzes Blackboard Discussion |
| literature / references | The literature list provides pointers for complementary reading only and will be updated before the start of the course:
M. van Steen, A. S. Tanenbaum. Distributed Systems. Ed. 3.01. 2017. ISBN 978-1543057386. |
| evaluation of teaching | |