Efficient active probing for fault diagnosis in large scale and noisy networks

Proceedings - IEEE INFOCOM

Volumn , Issue , 2010, Pages

  Cheng, Lu ^a   Qiu, Xuesong ^a   Meng, Luoming ^a   Qiao, Yan ^b   Boutaba, Raouf ^a  

^a BEIJING UNIVERSITY OF POSTS AND TELECOMMUNICATIONS   (China)

^b UNIVERSITY OF WATERLOO   (Canada)

Author keywords

Bayesian networks; Fault diagnosis; Information theory

Indexed keywords

ACTIVE PROBING; COMPUTATION TIME; EFFECTIVE TOOL; FAULT DIAGNOSIS; FAULT SCENARIOS; INFRASTRUCTURE COSTS; MONITORING NETWORK; OPTIMAL SETS; SMALL SIZE; STRUCTURE PROPERTY;

ADAPTIVE ALGORITHMS; COMPUTATIONAL COMPLEXITY; COST REDUCTION; DISTRIBUTED PARAMETER NETWORKS; FAILURE ANALYSIS; INFERENCE ENGINES; INFORMATION THEORY; INTELLIGENT NETWORKS; OPTIMIZATION; PROBES;

BAYESIAN NETWORKS;

EID: 77953299785     PISSN: 0743166X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/INFCOM.2010.5462041     Document Type: Conference Paper

References (26)

1. G. Jakobson and M. Weissman. Alarm Correlation. IEEE Network, 1993.
2. S. A. Yemini, S. Kliger, E. Mozes, Y. Yemini, and D. Ohsie. A Coding Approach to Event Correlation. In Proc. IM'95, Pages 266-277, 1995.
3. M. Brodie, I. Rish, S. Ma, N. Odintsova, and A. Beygelzimer. Active Probing Strategies for Problem Diagnosis in Distributed Systems. In Proc. IJCAI'03, 2003
4. I. Rish, M. Brodie, N. Odintsova, S. Ma, and G. Grabainik. Real-time problem determination in distributed systems using active probing. In Proc. NOMS'04, pages 133-146, 2004.
5. I. Rish, M. Brodie, S. Ma, N. Odintsova, A. Beygelzimer, G. Grabainik, and K. Hernandez. Adaptive Diagnosis in Distributed Systems. IEEE Trans. Neural Networks, 16(5):1088-1109, 2005.
6. Y.Tang, E. Al-Shaer, and R. Boutaba. Active Integrated Fault Localization in Communication Networks. In Proc. IM'05, France, 2005.
7. Y. Tang, E. Al-Shaer, and R. Boutaba. Efficient fault diagnosis using incremental alarm correlation and active investigation for internet and overlay networks. IEEE Trans. Network and Service Management, 5(1): 36-49, 2008
8. M. Natu and A. S. Sethi. Probabilistic Fault Diagnosis Using Adaptive Probing. In Proc. DSOM, LNCS 4785, pp. 38-49, 2007.
9. M. Natu and A. S. Sethi. Application of Adaptive Probing for Fault Diagnosis in Computer Networks. In NOMS'08, pp:1055-1060, 2008.
10. L. Cheng, X.S. Qiu, L.M. Meng, Y. Qiao and Z.Q. Li. Probabilistic Fault diagnosis for IT Services in Noisy and Dynamic Environments. In Proc. IM'09, New York, June 2009.
11. D. V. Lindley. On a measure of the information provided by an experiment. Annals of Mathematical Statistics, 27:986-1005, 1956.
12. A. X. Zheng, I. Rish, and A. Beygelzimer. Efficient test selection in active diagnosis via entropy approximation. In Proceedings of Uncertainty in AI (UAI' 05), 2005
13. J. Pearl. Probabilistic reasoning in intelligent systems: networks of plausible inference. Morgan Kaufmann, San Mateo, California, 1988.
14. K. P. Murphy, Y. Weiss, and M. Jordan. Loopy belief propagation for approximate inference: an empirical study. In Proceedings of Uncertainty in AI(UAI' 99), pages 467-475, 1999.
15. S. Kandula, D. Katabi, and J. P. Vasseur. Shrink: A tool for failure diagnosis in IP networks. In Proc. ACM SIGCOMM MineNet Workshop, Aug. 2005.
16. S. Kullback. The Kullback-Leibler distance. The American Statistician, 41:340-341, 1987.
17. R. G. Cowell, A. P. Dawid, S. L. Lauritzen, D. J. Spiegelhalter. Probabilistic Networks and Expert Systems. Springer-Verlag, New York, 1999
18. K. P. Murphy. The Bayes Net Toolbox for Matlab. In Computing Science and Statistics: Proceedings of the Interface, volume 33, 2001.
19. N. Odintsova and I. Rish. Empirical Study of Topology Effects on Diagnosis in Computer Networks. In Proc. Mobile Adhoc and Sensor Systems, 2007.
20. B. M. Waxman. Routing of multipoint connections. IEEE Journal on Selected Areas in Communications, 6(9):1617-1622, 1988.
21. M. Faloutsos, P. Faloutsos, and C. Faloutsos. On power-law relationships of the Internet topology. ACM SIGCOMM Computer Communication Review, 29(4):251-262, 1999.
22. J. Winick and S. Jamin. Inet-3.0: Internet topology generator. Technical Report CSE-TR-456-02, University of Michigan, 2002.
23. T. Jaakkola and M. Jordan. Variational probabilistic inference and the qmr-dt database. Journal of Artificial Intelligence Research, pages 291-322, 1999.
24. M. Steinder and A.S. Sethi. Increasing Robustness of Fault Localization through Analysis of Lost, Spurious and Positive Symptoms. In Proc. IEEE INFOCOM, 2002.
25. R. R. Kompella, J. Yates, A. Greenberg, and A. Snoeren. Detection and Localization of Network Black Holes. in Proc. IEEE INFOCOM, 2007.
26. H.H. Song, L.L. Qiu and Y. Zhang. NetQuest: A Flexible Framework for Large-Scale Network Measurement, in Proc. ACM SIGMETRICS, Saint-Malo, France, June 2006.