Performance Impact of Error Correction Codes in RNS with Returning Methods and Base Extension
Egor M. Shiriaev, Ekaterina Bezuglova, Mikhail Grigoryevich Babenko, Andrei Nikolaevitch Tchernykh, Luis Bernardo Pulido-Gaytan, Jorge M. Cortés-Mendoza · 2021
In this paper, we study techniques of correction codes for systems based on the Residue Number System (RNS). Self-correcting and error detection are important properties of RNS that allow the development of distributed data storage systems. However, the complexity of several approaches have a significant influence on system performance, it mostly depends on two methods: expanding the number base in the residual class and converting numbers from the residual system to the positional system. In this work, we review the state-of-the-art methods in the field and show that the most efficient error correction method combines the syndrome method and our method to expand the number base.