Rastgele Sayıların Mikrodenetleyici Platormunda Üretilmesi

Year 2024, Volume: 16 Issue: 2, 668 - 678, 30.06.2024

Mustafa Sanlı

https://doi.org/10.29137/umagd.1392479

Abstract

Mikrodenetleyiciler ucuz ve çok yönlü olmaları nedeniyle günlük uygulamalarda yaygın olarak kullanılmaktadır. Son yıllarda Nesnelerin İnterneti ve Yapay Zeka alanlarında yaşanan gelişmeler mikrodenetleyicilerin uygulama alanlarını daha da artırmıştır. Mikrodenetleyici uygulamalarının en büyük sorunu, mevcut sınırlı donanım kaynaklarıyla rastgele sayıların üretilmesidir. Farklı saat kaynaklarındaki seğirmeyi kullanan veya özel rastgele sayı üreteçleri içeren mevcut yöntemler, ya çalışma hızından yoksundur ya da pahalı donanım bileşenlerinin eklenmesini gerektirir. Bu makale, bir mikrodenetleyici platformunda rastgele sayılar üretmek için bir transistördeki çığ kırılma belirsizliğini kullanmaktadır. Bu çalışma kapsamında rastgele sayılar üretecek bir donanım platformu tasarlanmış ve üretilen veriler istatistiksel yöntemlerle analiz edilmiştir. Sunulan çözüm hem tasarım bütçesi hem de donanım kaynakları açısından oldukça hızlı ve uygun maliyetlidir.

Keywords

Mikrodenetleyici, RNG, IoT

Generation of Random Numbers on a Microcontroller Platform

Abstract

Microcontrollers are widely used in everyday applications as a result of their cheap and versatile nature. Recent advances in the fields of Internet of Things and Artificial Intelligence further increased the application areas of microcontrollers. A major problem of microcontroller applications is the generation of random numbers with the limited hardware resources available. Existing methods which use the jitter in different clock sources or incorporate dedicated random number generators either lack operation speed or need addition of expensive hardware components. This paper uses the avalanche breakdown uncertainty in a transistor to generate random numbers on a microcontroller platform. In the context of this study, a hardware platform is designed to generate random numbers and generated data is analyzed through statistical methods. The presented solution is quite fast and cost effective in terms of both design budget and hardware resources.

Keywords

Microcontroller, RNG, IoT

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