Randomness is not of the computer world. Strange as it may seem, reproducing random behaviors such as throwing the dice or heads or tails with software is far from easy. Computers, at least as they are conceived today, are designed and built to blindly perform the operations that are fed to them by means of algorithms and programs made by developers. A computer that does not follow the instructions and should “take the initiative” could be considered, rightly, broken or malfunctioning.

And to say that random numbers can be very useful also and above all in the field of modern computing. Thanks to these values, for example, it is possible to construct an unassailable cryptographic key or to select random items within large datasets (Big data, for example) to carry out statistical and scientific analyzes.

For this reason, over the years and decades, a growing number of developers and computer scientists focused on developing algorithms that could at least simulate the selection of random numbers. An enterprise that is anything but simple and which today follows two distinct “philosophies of thought”: PRNG (an acronym for Pseudo-Random Number Generator) and TRNG (an acronym for True Random Number Generator).

What are random numbers in Bingo?

Before proceeding and discovering how to generate random numbers, it is worth dwelling for a few seconds on a definition of what random numbers are. In the case of single digits, a number is random when it is chosen within a given set (all natural numbers, for example, or only those from 1 to 100) without following a precise rule. If, on the other hand, we are talking about sequences of random numbers, the chosen figures must not have any statistical correlation that binds them to each other,  this system applies to all games of chance software and bingo is no exception.

One of the most loved games is bingo. Especially during the winter, it can be handy knowing how to organize a Bingo with friends in the evening so you can spend some leisure time in good company. Online bingo today uses software that implements an RGN to generate a series of random numbers during the game. You can play bingo from home with friends connected all over the world thanks to the internet and websites that allow many players to chat and spend time with new friends.

How PRNG models work?

As the suffix “Pseudo” suggests, software using this technique generates a sequence of numbers that appear to be random but are not at all. A good example of PRNG generators is given by linear congruent generators, which allow generating strings of numbers sufficiently close to randomness. In short, it will not be like rolling the dice but it gets very close. A result that is obtained thanks to algorithms that follow a precise mathematical formula or by following the series of numbers present in a previously calculated and compiled table.

PRNG models are efficient and deterministic. This means that they generate large sequences of random numbers in a very short period of time and, given the same starting value, they allow to reproduce exactly the same string of pseudo-random numbers. Features that make these models suitable for operations that require speed and reproducibility such as, for example, the simulation of statistical models. If, on the other hand, you need to generate truly random numbers – as required in the case of online gambling or cryptography – it is best to look towards other models.

It should be noted, in fact, that no matter how perfect and perfected, PRNG models can lead to inconsistencies that are anything but secondary. Thus, if you generate a PRNG model with PHP and use it on Linux systems you will have very few problems; while if you are using a Windows system you could experience many problems.

How TRNG models work?

The True Random Number Generators, on the other hand, link their functioning to physical phenomena to generate – as the name implies – real random numbers. In short, it will be like bringing the roll of the dice into the computer. The events that can cause the generation can be the most varied: from the movement of the mouse to the typing of the keys, to more strictly physical phenomena. Many software and random number generation portals, for example, exploit the decay of radioactive elements, while others exploit atmospheric noise recorded with normal microphones. In short, the sources can be the most varied: the important thing is to avoid noises or events that repeat themselves over time, so as to generate truly random sequences of numbers.

Given its nature, the TRNG model has diametrically opposite characteristics to those seen in the PRNG model. The True Random Number Generator, in fact, is neither efficient nor deterministic: the generation of random numbers is linked to physical factors and is not as fast and immediate as previously seen; in the same way, the sequence of numbers cannot be reproduced since it is linked to events totally unrelated to each other. The TRNG model, therefore, is ideal for applications such as cryptography or online gambling, for which absolute randomness of the numbers is fundamental.

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