Network Support Data Analysis for Fault Identification Using Machine Learning

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Author(s): Shakila Basheer (King Khalid University, Abha, Saudi Arabia), Usha Devi Gandhi (VIT University, Vellore, India), Priyan M.K. (VIT University, Vellore, India)and Parthasarathy P. (VIT University, Vellore, India)
Copyright: 2022
Pages: 10
Source title: Research Anthology on Machine Learning Techniques, Methods, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-6684-6291-1.ch031

Keywords: Artificial Intelligence / Engineering Science Reference / Knowledge Management and Library Science / Machine Learning

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Abstract

Machine learning has gained immense popularity in a variety of fields as it has the ability to change the conventional workflow of a process. The abundance of data available serves as the motivation for this. This data can be exploited for a good deal of knowledge. In this article, we focus on operational data of networking devices that are deployed in different locations. This data can be used to predict faults in the devices. Usually, after the deployment of networking devices in customer site, troubleshooting these devices is difficult. Operational data of these devices is needed for this process. Manually analysing the machined produced operational data is tedious and complex due to enormity of data. Using machine learning techniques will be of greater help here as this will help automate the troubleshooting process, avoid human errors and save time for the technical solutions engineers.

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Network Support Data Analysis for Fault Identification Using Machine Learning

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