Adaptive Data Storage, Transmission and Processing System in Fog Computing Using Residue Number System and Artificial Neural Networks

Abstract

The article presents an adaptive data storage, transmission, and processing system for fog computing environments, leveraging the Residue Number System and Artificial Neural Networks. The proposed architecture demonstrates advantages in reliability, safety, scalability, resource efficiency, and adaptability compared to existing methods. The proposed architecture demonstrates the potential for creating adaptive and fault-tolerant computing platforms.