Network Failure Identification System

Abstract

In this paper, a remedy to reduce the man power when there is failure in the network is presented. Communication (network) faultscan cause delays or even shutdown of the entire manufacturing process. The current process of detecting and diagnosing communication faults is mostly manual, cumbersome, and inefficient. Detecting early symptoms of potential problems is very important but automated solutions do not yet exist. Our research goal is to automate the process of detecting and diagnosing the communication faults as well as to prevent problems by detecting early symptoms of potential problems. To achieve our goal, we have first investigated real-world fault cases and summarized control network failures and also defined alarm conditions to detect early symptoms. Researchers have approached this problem using various techniques such as artificial intelligence, machine learning, and state machine modelling. But we are using processing technique based on abrupt change detection. The application of processing techniques to this area is still in its infancy, and we believe that it has great potential to enhance the field, and thereby improve the reliability of IP networks.