Practical Byzantine Fault Tolerance is a consensus algorithm introduced in the late 1990s by Barbara Liskov and Miguel Castro. pBFT was designed to work effectively in asynchronous systems (no ceiling for receiving the response to demand). It is optimized for low overhead time. Its aim was to solve many problems related to the Byzantine error tolerance solutions already available. Application domains include distributed computing and blockchain. What is the Byzantine margin of error? The Byzantine Margin of Error (BFT) is the characteristic of a distributed network to reach consensus (agreement on the same value), even if some network nodes do not respond or react with false information. The objective of a BFT mechanism is to protect system failures by using collective decision-making (correct and erroneous nodes) to reduce the influence of defective nodes. BFT derives from the problem of Byzantine generals. Even if the first message passes, General 2 must recognize (ACK, note the resemblance to the 3-way TCP handshake) that he received the message, so he returns a messenger and repeats the previous scenario in which the messenger can be caught. This extends to infinity and therefore the generals are not in a position to reach an agreement.
This problem (first published in 1975 and named by its name in 1978) describes a scenario in which two generals attack a common enemy. General 1 is considered a leader and the other is considered a successor. Any general`s army alone is not enough to defeat the enemy army, so they must cooperate and attack at the same time. This seems to be a simple scenario, but there is a restriction: Leslie Lamport has proven that if we have processors running properly 3m-1, a consensus (an agreement on the same state) can be reached if most m processors are defective, meaning that strictly more than two-thirds of the total number of processors should be honest. The problem is complicated by the presence of insidious generals, who vote not only in favour of a suboptimal strategy, but also selectively. For example, if nine generals vote, four of whom support an attack, while four others are in favour of withdrawal, the ninth general may send a withdrawal vote to these generals in favour of withdrawal and one vote to attack the rest. Those who have obtained a withdrawal vote from the ninth general will withdraw while the rest will attack (which may not be good for the attackers). The problem is further complicated by the fact that generals must be physically separated and send their votes through messengers who might not vote or falsify false votes. Byzantine Generals Problem The problem was rightly explained in a document by LESLIE LAMPORT, ROBERT SHOSTAK and MARSHALL PEASE at Microsoft Research in 1982: in the end, a validator is chosen to generate a new block based on their economic participation in the network. Therefore, poS encourages auditors to reach an agreement through an incentive mechanism. In this article, we discussed some general information on the problem of consensus in distributed systems.
(see  for proof of impossibility). The problem is usually taken up in the form of a commanding general and loyal lieutenant, the general being either loyal or a traitor, and the same for lieutenants in the following qualities. The objective of the Byzantine margin of error is to protect against system component failures, with or without symptoms, preventing other components of the system from reaching an agreement if such an agreement is necessary for the system to function properly.