Distributed computing systems arise in a wide range of modern applications. This course surveys the foundations of many distributed computing systems, namely, the distributed algorithms that lie at their core. The course provides the basis for designing distributed algorithms and formally reasoning about their correctness. It addresses issues related to what distributed systems can and cannot do (i.e., impossibility results) in certain system models.
The course focuses on three aspects of distributed computing: system models, fundamental problems in distributed computing, and application of distributed algorithms. System models include synchronous versus asynchronous systems, communication models, and failure models. Several fundamental problems are covered, including consensus, atomic broadcast, atomic multicast, atomic commit, and data consistency. Applications of distributed algorithms target various forms of replication techniques.
Students will learn by following classes, reading suggested material, doing assignments, and working on a project.
The overall course grade is based on a midterm exam, a project, assignments, and a final exam.
Conference and journal papers, handouts and online documents.
Master of Science in Computational Science, Elective course, 1st year
Master of Science in Computational Science, Elective course, 2nd year
Master of Science in Economics in Finance, Elective course, Minor in Digital Finance, 2nd year
Master of Science in Financial Technology and Computing, Core course, 2nd year
Master of Science in Informatics, Elective course, 1st year
Master of Science in Informatics, Elective course, 2nd year
PhD programme of the Faculty of Informatics, Elective course, Lecture, 1st year (4 ECTS)
PhD programme of the Faculty of Informatics, Elective course, Lecture, 2nd year (4 ECTS)