Distributed Algorithms

Image of a honeycomb, with four rows of hexagons.

The honeycomb shown above is a common architectural metaphor for distributed algorithms. Similar to bees performing different functions to build a honeycomb, multiple computing devices depend on each other to accomplish a task. (Image by MIT OpenCourseWare.)

Instructor(s)

MIT Course Number

6.852J / 18.437J

As Taught In

Fall 2009

Level

Graduate

Cite This Course

Course Description

Course Features

Course Description

Distributed algorithms are algorithms designed to run on multiple processors, without tight centralized control. In general, they are harder to design and harder to understand than single-processor sequential algorithms. Distributed algorithms are used in many practical systems, ranging from large computer networks to multiprocessor shared-memory systems. They also have a rich theory, which forms the subject matter for this course.

The core of the material will consist of basic distributed algorithms and impossibility results, as covered in Prof. Lynch's book Distributed Algorithms. This will be supplemented by some updated material on topics such as self-stabilization, wait-free computability, and failure detectors, and some new material on scalable shared-memory concurrent programming.

Other Versions

Related Content

Nancy Lynch. 6.852J Distributed Algorithms. Fall 2009. Massachusetts Institute of Technology: MIT OpenCourseWare, https://ocw.mit.edu. License: Creative Commons BY-NC-SA.


For more information about using these materials and the Creative Commons license, see our Terms of Use.


Close