Reliability Analysis in Cyber-Physical System Using Deep Learning for Smart Cities Industrial IoT Network Node

Abstract

AbstractThe reliability, availability, security, and survivability analysis of any IoT (Internet-of-things) device is important because it provides all necessary information about the IoT device applications for smart city development to improve its performance of smart cities’ Industrial IoT Network Node. The in-depth knowledge about the IoT Device Applications to be analyzed from a parameters point of view is needed, which inspires the researcher to understand the IoT Device network system very profoundly in terms of Cyber-Physical System (CPS). Until now, less attention is being given to the reliability analysis of smart city-based Industrial IoT devices and Cyber-Physical Systems (CPS). The root failure causes a cyber-attack. The analysis provides the base failure causes, the information about the type of failures and estimates the various reliability parameters. Through this analysis, a better design, a better manufacturing process in Smart Cities, Industrial IoT devices, preventive and corrective maintenance, redundancy, etc., we can easily be recommended for better performance of the device or CPS Using Deep Learning for Smart Cities based Industrial IoT Device (IIOT) Applications. The proposed technique is useful for addressing the system's dependability, design, and development since it can correctly and efficiently analyze the IoT network's reliability.KeywordsSmart citiesReliability analysisInternet-of-thingsIndustrial IoT device