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TU Berlin

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Master Project: Distributed Systems


Kick-off meeting
Wednesday, April 20, at 2 pm
E-N 152
Weekly meeting
Weekly, to be announced 
E-N 057


  • This project is limited to 30 students (which will be subdivided into teams of 5 to 10 students)
  • The participation requires a registration.
  • To register, please write an email to the contact person (see contact on the right).
  • The final list of participants will be determined in the kick-off meeting.

Target Audience

Master students with advanced programming skills, who would like to gain experience in working on a larger project from the area of distributed and complex IT systems.


In different areas of everyday life, social networks are used to connect people and collect data, which can be processed and analyzed in order to generate value for the users. There is a broad spectrum of relevant applications, ranging from more general-purpose social networks like Instagram to more specific social networks that connect particular target groups like patients. In the latter case, for example, such a network can enable new kinds of patient-to-patient, patient-to-physician, as well as physician-to-physician interactions. The data collected can be used in order to motivate the patient, keep everyone involved up-to-date, provide feedback on the treatment (when health-related sensors are connected) and thereby optimize the overall process. However, it is a challenge to design a social network, since short update cycles based on user feedback are necessary and each modification incurs substantial costs. A second, similarly important challenge is the preservation of user data privacy.

In order to cope with these challenges, the members of this project will develop a construction kit (dt. "Baukasten") for privacy-preserving social networks. For this, they will abstract common features from currently existing social networks and use them to develop a meta model, which will serve as basis for social network specification. They can use already existing work on the model part, the Apache Flink framework in order to process data, as well as the result of the Bachelor project from the winter semester: a scalable, distributed social network for data scientists. Since privacy has become an important asset, the construction kit will enable the separation between non-private and private data, which will not (or only with restrictions) be accessible by the social network providers. In the final product, social network providers will be able to define a model-based description of the desired social network, style templates and privacy preferences, in order to automatically generate the desired social network, which will be distributed, scalable and run out-of-the-box.

The project management part will be based on the latest practices of agile software development. Before the start of the actual project, project management techniques and key technologies will be introduced.

Technologies and languages that will be used (in alphabetical order):

  • Android IDE
  • Apache Flink
  • Django
  • Docker
  • Java
  • nginx
  • Python
  • Swift with XCode
  • Web Services

Project management methods:

  • Scrum or
  • Kanban

At the beginning of the project, focus areas will be determined, so that each student can choose to specialize on a particular area of his or her interest.


Advanced programming skills in any language; interest in distributed systems and social media.

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