Design and Implementation of an Intelligent Expert System for Automated Network Diagnosis

International Journal of Computer Science and Technology | Vol. 12, No. 2, February 2010 | pp. 9–16

DOI: 10.46882/2010/IJCST/000023

Article Type: Research Paper

Title: Design and Implementation of an Intelligent Expert System for Automated Network Diagnosis

Names of Authors: Tim J. Berners-Lee¹, Vinton G. Cerf²

Authors’ Affiliations: ¹World Wide Web Laboratory, CERN, Geneva, Switzerland; ²Department of Telecommunications, Stanford University, California, USA

Abstract: Network downtime in enterprise systems often results in severe economic and operational losses, requiring rapid fault localization tools. This article covers the design and deployment of the Intelligent Network Diagnostics Expert System (IND-ES), a knowledge-based framework for automated router and switch troubleshooting. IND-ES applies a forward-chaining inference engine combined with semantic rule bases to interpret system syslog messages and SNMP traps in real time. We evaluated the expert system within a production university network connecting over 8,000 host nodes. The empirical results show that IND-ES isolates network routing loops, packet drops, and interface failures with an accuracy rate of 95.4%. The average time to diagnose a critical core network failure decreased from 42.1 minutes using human analysis to 1.8 seconds using the automated engine. The findings prove that rule-based AI systems provide highly effective support for network engineers managing complex topologies.

Keywords: Expert Systems, Network Diagnosis, Knowledge Representation, Inference Engine, Network Management, Troubleshooting Automation

Manuscript Timeline: Received: June 20, 2009; Revised: August 15, 2009; Accepted: September 10, 2009; Published: February 22, 2010

Citation: Berners-Lee, J. T., & Cerf, V. G. (2010). Design and Implementation of an Intelligent Expert System for Automated Network Diagnosis. International Journal of Computer Science and Technology, 12(2), 9–16.

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