Byzantine Agreement Problem

What my son doesn`t yet know or understand (apart from the answer) is the profound impact of the problem and the practical application of the solution mentioned in Satoshi Nakamoto`s 2008 paper titled „Bitcoin: A Peer-to-Peer Electronic Cash System.“ ► The proposal of an error tolerance scheme for distributed systems is an important issue. ► Previous minutes have required numerous rounds of message exchange and are ineffective. ► The concept of a reliable processor is proposed to reach an agreement, even if there are a large number of processors. ► The EARLY AGREEMENT WITH COMPARISON (CAE) protocol requires only three rounds of message exchange; This will improve overall performance. To make it easier to understand the interactive problem of consistency, Lamport devised a colorful allegory in which a group of army generals formulate a plan of attack against a city. In its original version, the story focused on the generals as commanders of the Albanian army. The name was changed and eventually based on „Byzantine“, at the proposal of Jack Goldberg, to ensure any insult to the future. [10] This formulation of the problem, along with some additional results, was presented by the same authors in their 1982 paper „The Byzantine Generals Problem.“ [11] Byzantine chess is considered the most general and difficult class of errors among the modes of error. The Fail-Stop-Failure mode proves the simplest end of the spectrum. While Fail-Stop error mode simply means that the only way to fail is a node crash detected by other nodes, Byzantine errors do not imply any restrictions, meaning that the failed node can generate any data, including data that makes it appear as a functional node. Thus, Byzantine failures can confuse defect detection systems, making the margin of error more difficult. Despite the analogy, a Byzantine failure is not necessarily a safety issue with hostile human interventions: it can be purely due to electrical or software errors.

The solution to the problem lies in an algorithm that can guarantee it: in this article, we discussed some general information about the problem of consensus in distributed systems. Studies by Pease, Shostak, and Lamport were among the first to address the problem of achieving coordinated behavior between processors in a distributed system in the event of a failure [21]. Since the publication of the work, this theme has become a vast field of research. Below is a presentation of the main findings on the specific issues addressed in their paper. In some cases, this entry uses the terminology currently accepted in this field and not the original terminology used by the authors. Before considering possible solutions to this problem, let me sketch out the problem more specifically and explain how it relates to you and your business. Loyal lieutenants will do whatever the algorithm says, but traitors can do anything they want. The algorithm must guarantee the first condition, no matter what the traitors do. Loyal lieutenants should not only reach an agreement, but agree on a reasonable plan. Several solutions were described in 1982 by Lamport, Shostak and Pease.

[11] They began by saying that the problem of generals can be reduced to the solution of a „commander and lieutenant“ problem, where loyal lieutenants must all act together and that their action must be in accordance with what the commander has ordered if the commander is loyal: reliability is an important research topic in distributed computer systems, consisting of a large number of processors.