Distributed Systems

Students must have a Bachelors degree in computer science or related field.

More specifically students must have programming skills, knowledge about operating systems, networking and computer organisation/architectures including basic understanding of concurrency problems in uniprocessor environments.

After the course, a student can 

• explain the key principles of distributed system development
• apply the principles in evaluating major design paradigms used in implementing distributed systems
• describe distributed decision-making and some alternatives used in it
• explain challenges and solutions related to key issues of distributed systems, including coordination, consistency, replication, and fault tolerance

• apply distribution techniques when designing and implementing distributed systems

• use different levels of abstraction when discussing about basic distributed system techniques and distribution challenges as well as presenting solutions for these challenges

• combine together the common solutions of different focus areas (like replica management, data consistency models and management, and agreements between untrusted agents) 

• identify distribution benefits and disadvantages  and estimate effects of inter-dependencies of different solutions. 

In addition, student will learn general skills that include at least time management, group work, problem solving, documentation, implementation.

The course is partially based on the course books, including Maarten van Steen (Avautuu uuteen välilehteen)and Andrew S Tanenbaum(Avautuu uuteen välilehteen) Distributed Systems – Principles  and Paradigms, Third Edition, 2017, and/or Sukumar Ghosh: Distributed systems an algorithmic approach, 2nd edition, Chapman&Hall/CRC, 2015. Any other distributed systems textbook covering the topics of the course is also possible to use.

Supplementary on-line material will be provided during the course as needed via course moodle.

Completion methods

1. Participation in teaching: weekly exercise sessions (non-mandatory but yield course points), group project, and a course exam.
2. The course can be passed by taking a separate exam after independent study of the course materials.
3. This course may be arranged in a different format and with different assessment methods for open university students.
   

Assessment practices and criteria

Course is graded on the scale 0...5. 5/6 or more of course points yields grade 5 and 1/2 of the points yields grade 1.

Part of the points needed to pass the course come from the exercises, part from group project and part from the exam. Group project is graded, exercises are self-evaluated during the meetings.

The exams contain questions that test the students' learning according to the goals set in the learning objectives.

Activities and teaching methods in support of learning

Lectures and weekly exercise sessions support the learning and checking of understanding the central topics of the course content. Group work supports the development of co-operative skills and enhances understanding of the topics because of the need to arrive at a shared understanding of the problems and the prototype implementation of the solutions. The written documents and demonstrations enhance the presentations skills. The weekly schedule with deadlines for the assignments creates a steady rhythm for the work.

Target groups

Optional course in a compulsory module for all students of the Programme. Available also to students from other degree programmes. Suitable for exchange students (if prerequisites met).

Recommended time/stage of studies for completion

First autumn of studies

Term/teaching period when the course will be offered

Yearly in the 2. period

Study module

Core advanced courses in computer science

Expiry of studies

Default rules apply

Language of instruction

English