Fault Tolerant System for Data Storage, Transmission and Processing in Fog Computing Using Artificial Neural Networks

Abstract

The emergence of the Internet of Things (IoT) has led to the adoption of fog computing as a highly advantageous system for connecting IoT devices. However, to ensure seamless operation within fog computing networks, there is a need for robust software and systems. Artificial Neural Networks (ANN) have shown significant potential in improving data storage, transmission, and processing systems in fog computing environments. This study aims to review various applications of ANNs within fog computing systems. The research highlights the advantages of ANN in enhancing the efficiency and effectiveness of data management, considering factors such as data storage, transmission, and processing. The study presents different use cases where ANN have been applied in fog computing networks, demonstrating their ability to optimize data classification, facilitate real-time decision-making, and enhance the usability of fog computing for workers.