Abstract
In this paper, we present a framework for supporting intelligent fault and performance management for communication networks. Belief networks are taken as the basis for knowledge representation and inference under evidence. When using belief networks for diagnosis, we identify two questions: When can I say that I get the right diagnosis and stop? If right diagnosis has not been obtained yet, which test should I choose next? For the first question, we define the notion of right diagnosis via the introduction of intervention networks. For the second question, we formulate the decision making procedure using the framework of partially observable Markov decision processes. A heuristic dynamic strategy is proposed to solve this problem and the effectiveness is shown via simulation.
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References
J. S. Baras, H. Li and G. Mykoniatis, “Integrated, Distributed Fault Management for Communication Networks”, Technical Report, CSHCN TR 98-10, University of Maryland, 1998
D. P. Bertsekas, Dynamic Programming and Optimal Control, Vol. I and II, Athena Scientific, Belmont, MA, 1995
D. P. Bertsekas, and J. N. Tsitsiklis, Neuro-Dynamic Programming Athena Scientific, 1996
T. M. Cover, and J. A. Thomas, Elements of Information Theory, Wiley Interscience, 1991
Gabrijela Dreo, “A Framework for Supporting Fault Diagnosis in Integrated Network and Systems Management: Methodologies for the Correlation of Trouble Tickets and Access to ProblemSolving Expertise”, PhD Dissertation, Department of Computer Science, University of Munich, 1995
G. Goldszmidt, Y. Yemini, “Distributed Management by Delegation”, in Proceedings of 15thInternational Conference on Distributed Computing Systems, 1995
D. Heckerman, J. S. Breese, and K. Rommelse, “Decision-Theoretic Troubleshooting”, Communications of the ACM vol. 38, pp. 49–57, 1995
H.G. Hegering, S. Abeck, and B. Neumair. Integrated Management of Networked Systems: Concepts, Architectures, and Their Operational Application. Morgan Kaufmann, San Francisco, CA, USA, 1999.
C. S. Hood, and C. Ji, “Probabilistic Network Fault Detection”, GlobalCom pp. 1872–1876, 1996
J. Huard, and A. A. Lazar, “Fault Isolation based on Decision-Theoretic Troubleshooting”, Tech. Rep. TR 442-96-08, Center for Telecommunications Research, Columbia University, 1996
G. Jacobson, M. Weissman, “Alarm Correlation”, IEEE Network Vol. 7, No. 6, 1993
J. Kalagnanam and M. Henrion, “A Comparison of Decision Analysis and Expert Rules for Sequential Diagnosis”, in Uncertainty in Artificial Intelligence 4 pp. 271–281, Elsevier Science Publishers B. V., 1990
L. Kerschberg, R. Baum, A. Waisanen, I. Huang and J. Yoon, “Managing Faults in Telecommunications Networks: A Taxonomy to Knowledge-Based Approaches”, IEEE, pp. 779–784, 1991
L. P. Kaelbling, M. L. Littman, and A. R. Cassandra, “Planning and acting in partially observable stochastic domains”, Artificial Intelligence, Vol 101, pp. 99–134, 1998
S. Kliger, S. Yemini, Y. Yemini, D. Ohsie, and S. Stolfo. “A Coding Approach to Event Correlation.” In Sethi, Raynaud, and Faure-Vincent, editors, Integrated Network Management, no. 4, pp. 266–277. May 1995.
A. Leinwand and K. F. Conroy, Network Management, A practical perspective, second edition, Addison-Wesley, 1996
H. Li, J. S. Baras and G. Mykoniatis, “An Automated, Distributed, Intelligent Fault Management System for Communication Networks”, ATIRP’99 1999
H. Li, S. Yang, H. Xi, and J. S. Baras, “Systems Designs for Adaptive, Distributed Network Monitoring and Control”, IFIP/IEEE International Symposium on Integrated Network Management Seattle, Washington, May 2001, to appear.
G. Mahamat, A. Das, G.V. Bochmann, “An overview of fault management in telecommunication networks”, Advanced Information Processing Techniques for LAN and MAN Management 1994 IFIP
R. Maxion, “A case study of ethernet anomalies in a distributed computing environment”, IEEE Trans. on Reliability, Vol. 39, No. 4, pp. 433–443, Oct 1990
J. Pearl, Probabilistic Reasoning In Intelligent Systems: Networks of Plausible Inference, Morgan Kaufmann, 1988
J. Pearl, Causality Cambridge Press, 2000
M. Sloman and K. Twidle. “Chapter 16. Domains: A Framework for Structuring Management Policy”. In M. Sloman (Ed.). Network and Distributed Systems Management pp. 433–453. Addison-Wesley, Wokingham, UK, 1994.
R. S. Sutton, A. G. Barto, Reinforcement Learning: An Introduction, MIT Press, 1998
C.J.C, H. Watkins, P. Dayan, “Q-learning”, Machine Learning, 8, pp. 279–292, 1992
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Li, H., Baras, J.S. (2001). A Framework for Supporting Intelligent Fault and Performance Management for Communication Networks. In: Al-Shaer, E.S., Pacifici, G. (eds) Management of Multimedia on the Internet. MMNS 2001. Lecture Notes in Computer Science, vol 2216. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45508-6_20
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DOI: https://doi.org/10.1007/3-540-45508-6_20
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