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227-0558-00L 7 Credits BSC , DR , MSC , WBZ D-BSSE , D-INFK , D-MATH , D-ITET , D-GESS

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Principles of Distributed Computing

Lecturers & Examiners: Prof. Dr. Roger Wattenhofer, Dr. Manuela Fischer

VVZ CR 3.84

Last Updated: 2026-06-01 11:33:06

Abstract

We study the fundamental issues underlying the design of distributed systems: communication, coordination, fault-tolerance, locality, parallelism, self-organization, symmetry breaking, synchronization, uncertainty. We explore essential algorithmic ideas and lower bound techniques.

Objective

Distributed computing is essential in modern computing and communications systems. Examples are on the one hand large-scale networks such as the Internet, and on the other hand multiprocessors such as your new multi-core laptop. This course introduces the principles of distributed computing, emphasizing the fundamental issues underlying the design of distributed systems and networks: communication, coordination, fault-tolerance, locality, parallelism, self-organization, symmetry breaking, synchronization, uncertainty. We explore essential algorithmic ideas and lower bound techniques, basically the "pearls" of distributed computing. We will cover a fresh topic every week.

Content

Distributed computing models and paradigms, e.g. message passing, shared memory, synchronous vs. asynchronous systems, time and message complexity, peer-to-peer systems, small-world networks, social networks, sorting networks, wireless communication, and self-organizing systems. Distributed algorithms, e.g. leader election, coloring, covering, packing, decomposition, spanning trees, mutual exclusion, store and collect, arrow, ivy, synchronizers, diameter, all-pairs-shortest-path, wake-up, and lower bounds

Resources

Lecture Notes

Available.

Literature

Lecture Notes By Roger Wattenhofer. These lecture notes are taught at about a dozen different universities through the world. Mastering Distributed Algorithms Roger Wattenhofer Inverted Forest Publishing, 2020. ISBN 979-8628688267 Distributed Computing: Fundamentals, Simulations and Advanced Topics Hagit Attiya, Jennifer Welch. McGraw-Hill Publishing, 1998, ISBN 0-07-709352 6 Introduction to Algorithms Thomas Cormen, Charles Leiserson, Ronald Rivest. The MIT Press, 1998, ISBN 0-262-53091-0 oder 0-262-03141-8 Disseminatin of Information in Communication Networks Juraj Hromkovic, Ralf Klasing, Andrzej Pelc, Peter Ruzicka, Walter Unger. Springer-Verlag, Berlin Heidelberg, 2005, ISBN 3-540-00846-2 Introduction to Parallel Algorithms and Architectures: Arrays, Trees, Hypercubes Frank Thomson Leighton. Morgan Kaufmann Publishers Inc., San Francisco, CA, 1991, ISBN 1-55860-117-1 Distributed Computing: A Locality-Sensitive Approach David Peleg. Society for Industrial and Applied Mathematics (SIAM), 2000, ISBN 0-89871-464-8

Learning Materials (Links)

Main link
Information
Recording
Recording

General Information

Language: English
Levels: BSC , DR , MSC , WBZ
Frequency: Yearly recurring

Examination

Type: session examination
Mode: written 120 minutes
Aids: All written documents (scripts, own notes, exercises, books, etc...) are allowed. All electronic devices (own calculator, mobile phone, laptop, etc...) are NOT allowed!

A grade bonus (0.25) can be achieved through designing an interesting exam-like question about the material of this course, complex enough to take about 20 minutes to solve. For details and deadlines seehttps://disco.ethz.ch/courses/podc/.

Course Components

Type	Title	Time & Place	Hours
lecture	Principles of Distributed Computing	Wed 08:15-10:00 (CAB G 61)	2 h weekly
exercise	Principles of Distributed Computing In Gruppen	Wed 14:15-16:00 (ETZ E 6) Wed 16:15-18:00 (ETZ E 6)	2 h weekly
independent project	Principles of Distributed Computing No presence required. Creative task outside the regular weekly exercises.	No time listed	2 h weekly

Offered In

Rechnergestützte Wissenschaften Bachelor
- Wahlfächer (Von den angebotenen Wahlfächern müssen mindestens zwei Lerneinheiten erfolgreich abgeschlossen werden.)
Rechnergestützte Wissenschaften Master
- Wahlfächer (Von den angebotenen Wahlfächern müssen mindestens zwei Lerneinheiten erfolgreich abgeschlossen werden.)
Informatik Master
- Vertiefungen
  - Vertiefung in Data Management Systems
    - Wahlfächer
- Ergänzungen
Computational Biology and Bioinformatics Master (More informations at: )
- Vertiefungsfächer (A total of 30 ECTS needs to be acquired in the Advanced Courses category. Thereof at least 16 ECTS in the Theory and 10 ECTS in the Biology category.)
  - Theorie (At least 16 ECTS need to be acquired in this category.)
Elektrotechnik und Informationstechnologie Master
- Master-Studium (Studienreglement 2018)
  - Vertiefung: Communication (The core courses and specialization courses below are a selection for students who wish to specialize in the area of "Communication", see . The individual study plan is subject to the tutor's approval.)
    - Kernfächer (These core courses are particularly recommended for the field of "Communication". You may choose core courses form other fields in agreement with your tutor. A minimum of 24 credits must be obtained from core courses during the MSc EEIT.)
      - Advanced Core Courses
  - Vertiefung: Computers and Networks (The core courses and specialization courses below are a selection for students who wish to specialize in the area of "Computers and Networks", see . The individual study plan is subject to the tutor's approval.)
    - Kernfächer (These core courses are particularly recommended for the field of "Computers and Networks". You may choose core courses form other fields in agreement with your tutor. A minimum of 24 credits must be obtained from core courses during the MSc EEIT.)
      - Advanced Core Courses
  - Vertiefung: Signal Processing and Machine Learning (The core courses and specialization courses below are a selection for students who wish to specialize in the area of "Signal Processing and Machine Learning ", see . The individual study plan is subject to the tutor's approval.)
    - Vertiefungsfächer (These specialization courses are particularly recommended for the area of "Signal Processing and Machine Learning", but you are free to choose courses from any other field in agreement with your tutor. Semester / Research Projects are not allowed in this category. A minimum of 40 credits must be obtained from specialization courses during the MSc EEIT.)
- Master-Studium (Studienreglement 2008)
  - Fächer der Vertiefung (A total of 42 CP must be achieved form courses during the Master Program. The individual study plan is subject to the tutor's approval. Semester / Research Projects are not allowed in this category.)
    - Communication
      - Kernfächer (Diese Fächer sind besonders Empfohlen, um sich in "Communication" zu vertiefen.)
    - Computers and Networks
      - Kernfächer (Diese Fächer sind besonders Empfohlen, um sich in "Computers and Networks" zu vertiefen.)
CAS in Informatik
- Vertiefungsfächer und Wahlfächer
Doktorat Informationstechnologie und Elektrotechnik (A minimum of 12 ECTS credit points must be obtained during doctoral studies (also see sub-categories for details) More Information at )
- Vertiefung Fachwissen (The courses on offer below are but a small selection out of a much larger available number of courses. Please discuss your course selection with your PhD supervisor.)
Science, Technology, and Policy Master
- Naturwissenschaftlich-technische Ergänzung
  - Daten und Informationstechnologie
Data Science Master
- Master-Studium (Studienreglement 2017)
  - Kernfächer
    - Wählbare Kernfächer
Cyber Security Master
- Ergänzung
  - Data Management Systems
    - Wahlfächer