Distributed Algorithms

Lectures: 30 h

Recommended for:
Computer science graduate students interested in networking, distributed operating
systems, and parallel computing.

The course last ran:
New course.

Goals:
To give students a broad overview of the different kinds of distributed sychronization
algorithms.

Prerequisites:
A course in algorithms and a course that includes concurrency control.

Organization:
Lectures and seminars.

Contents:
Distributed algorithms solve well known parallel computing problems (mutual exclusion) as well as problems typical for a distributed environment (routing). Topics include: Models of distributed algorithms, graph traversal distributed algorithms, minimal spanning tree construction, routing, synchronization algorithms, logical clocks, mutual exclusion in distributed models, leader election, Byzantine agreement, anonymous networks, global snapshot, detection of communication deadlock, centralized, hierarchical and distributed deadlock detection algorithms, and termination detection.

Literature:
G.Tel, Introduction to Distributed Algorithms, Cambridge University Press,1994.

Examiner:
Lenka Motyckova.

Schedule:
January - April 1999.

Examination:

Credit:
4 credits.

Page responsible: Director of Graduate Studies