Byzantine Generals’ Problem

Understanding the Byzantine Generals’ Problem

The concept of the Byzantine Generals’ Problem in computer science explores the possibility of achieving consensus in a computer network that consists of independent nodes spread across different locations.

In 1982, researchers from the SRI International Research Institute introduced this problem.

The scenario is as follows: a group of generals surrounding a city can only communicate through messengers. These generals must agree on a plan of action, whether to attack or retreat. However, some of the generals are traitors who actively work against reaching a consensus, and their identities are unknown.

The main question posed by this problem is what kind of decision-making algorithm the generals should use to devise a common plan, despite the interference of the traitors, and whether such an algorithm even exists.

According to the researchers’ analysis, it is indeed possible to create a system that can overcome this problem, but it requires that the number of loyal generals exceeds two-thirds. For example, if there are three generals and one of them is a traitor, the loyal generals can never guarantee reaching a consensus.

This problem holds significant relevance in the context of cryptocurrencies, as they essentially function as distributed computer systems. Cryptocurrencies consist of transaction-processing nodes that operate independently without any central authority and can only communicate remotely. These nodes are similar to the “generals” in the Byzantine Generals’ Problem, as they need to reach a consensus on which transactions have occurred and when.

Nodes in a cryptocurrency network have the potential to provide inaccurate transaction data either intentionally or unintentionally, and it is crucial to sort out this information. Bitcoin (BTC) and other cryptocurrencies address this problem through technical solutions like the proof-of-work and proof-of-stake algorithms.

For more information, see Byzantine Fault Tolerance (BFT).