Randomized protocols for asynchronous consensus

TL;DR

This paper reviews randomized protocols for asynchronous consensus, highlighting their role in overcoming the FLP impossibility by using randomness in distributed systems.

Contribution

It provides a detailed overview of the history, structure, and various protocols of randomized asynchronous consensus, emphasizing their significance.

Findings

Randomized protocols enable consensus in asynchronous systems despite failures.

Detailed descriptions of several key randomized consensus protocols.

Randomization is a crucial approach to circumvent FLP impossibility in distributed computing.

Abstract

The famous Fischer, Lynch, and Paterson impossibility proof shows that it is impossible to solve the consensus problem in a natural model of an asynchronous distributed system if even a single process can fail. Since its publication, two decades of work on fault-tolerant asynchronous consensus algorithms have evaded this impossibility result by using extended models that provide (a) randomization, (b) additional timing assumptions, (c) failure detectors, or (d) stronger synchronization mechanisms than are available in the basic model. Concentrating on the first of these approaches, we illustrate the history and structure of randomized asynchronous consensus protocols by giving detailed descriptions of several such protocols.