Performance impact of error correction codes in rns with returning methods and base extension

Abstract

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.