An Intelligent Methodology for Modeling Semantic Knowledge in Industrial Networks

Abstract

Networks has been involved in Industrial and IoT Applications for decades, creating new opportunities for more personalized services, improved security, greater automation and operational efficiency. Industry and businesses who prioritize and modernize their analytics strategy and technology to monetize their data will lead and succeed in our data-driven world. The network now provides even more detailed information through units and equipment databases, which provide details about the installed equipment, including models, designed capacity, performance and start / stop dates of the switches, routers, etc. repositories, digital files and business websites. Access to these collections is a serious challenge. Artificial intelligence and the Semantic Web provide a common framework for sharing and reusing knowledge in an efficient way. This article explores the architecture of intelligent agents to make the argument of an intelligent solution as opposed to traditional methods. We propose a new paradigm in which the intelligent management of the network is integrated into the conceptual repository of management information. This study focuses on an intelligent framework and language to formalize knowledge management descriptions and combine them with the existing SNMP management model. Based on the present proposal and the Internet management model, we describe the design and implementation of an integrated intelligent management platform called OntoNetwork.