Skip to main content
Log in

Automated network troubleshooting knowledge acquisition

  • Published:
Applied Intelligence Aims and scope Submit manuscript

Abstract

Troubleshooting knowledge acquisition is a notorious network maintenance expert systems development bottleneck. We present an improved methodology to generate automatically a skeleton of network troubleshooting knowledge base given the data about network topology, test costs, and network component failure likelihood. Our methodology uses AO * search where a suitable modification of the Huffman code procedure is found to be an admissible heuristic. Our heuristic uses synergistically information about both component failure rates and test costs while relaxing topology constraints. The resulting expert system (XTAR) minimizes expected troubleshooting cost faster and learns better troubleshooting techniques during its operation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. D. Peacocke and S. Rabie, “Knowledge-based maintenance in networks,” IEEE Journal on Selected Areas in Communications, vol. 6, no. 5, pp. 813–818, 1988.

    Google Scholar 

  2. Y. Lirov and O. Yue, “Expert maintenance systems in telecommunications,” forthcoming in Journal of Intelligent Systems, 1991.

  3. Y. Lirov, “Artificial intelligence methods in circuit packet troubleshooting—A survey,” Computers and Mathematics, vol. 18, no. 4, pp. 381–398, 1989.

    Google Scholar 

  4. A. Martelli and U. Montanari, “Optimizing decision trees through heuristically guided search,” Comm. of the ACM, vol. 21, pp. 1025–1039, 1978.

    Google Scholar 

  5. P. Varshney, C. Hartmann, and J.de Faria, “Application of information theory to sequential fault diagnosis,” IEEE Transactions on Computers, C 31(2), pp. 164–170, February 1982.

    Google Scholar 

  6. J. Slagle and C. Lee, “Application of game tree searching techniques to sequential pattern recognition,” Communications of the ACM, vol. 14, no. 2, pp. 103–110, February 1971.

    Google Scholar 

  7. T. Sheskin, “Sequencing of diagnostic tests for fault isolation by dynamic programming,” IEEE Transactions on Reliability, R 27(5), pp. 353–359, December 1978.

    Google Scholar 

  8. L. Duval, R. Wagner, Y. Han, D. Loveland, “Finding test-and-treatment procedures using parallel computation,” Journal of Parallel and Distributed Computing, vol. 4, pp. 309–318, 1987.

    Google Scholar 

  9. K. Pattipati and M. Dontamsetty, “Test sequencing in modular system,” in IEEE Conference on Systems, Man, and Cybernetics, Cambridge, MA, November 1989.

  10. A. Bagchi and A. Mahanti, “Admissible heuristic search in AND/OR graphs,” Theoretical Computer Science, vol. 24, pp. 207–219, 1983.

    Google Scholar 

  11. C. Chang and J. Slagle, “An admissible and optimal algorthm for searching AND/OR graphs,” Artificial Intelligence, vol. 2, pp. 117–128, 1971.

    Google Scholar 

  12. A. Mahanti and A. Bagchi, “AND/OR graph heuristic search methods,” Journal of the ACM, vol. 28, no. 1, pp. 28–51, January 1985.

    Google Scholar 

  13. L. Hyafil and R. Rivest, “Constructing optimal binary decision trees is NP-Complete,” Information Processing Letters, vol. 5, no. 1, pp. 15–17, May 1976.

    Google Scholar 

  14. D.A. Huffman, “A method for the construction of minimum redundancy codes,” Proc. IRE, vol. 40, pp. 1098–1101, 1962.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Lirov, Y., Yue, OC. Automated network troubleshooting knowledge acquisition. Appl Intell 1, 121–132 (1991). https://doi.org/10.1007/BF00058878

Download citation

  • Received:

  • Revised:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF00058878

Key words

Navigation