Abstract
Past research on probing-based network monitoring provides solutions based on preplanned probing which is computationally expensive, is less accurate, and involves a large management traffic. Unlike preplanned probing, adaptive probing proposes to select probes in an interactive manner sending more probes to diagnose the observed problem areas and less probes in the healthy areas, thereby significantly reducing the number of probes required. Another limitation of most of the work proposed in the past is that it assumes a deterministic dependency information between the probes and the network components. Such an assumption can not be made when complete and accurate network information might not be available. Hence, there is a need to develop network monitoring algorithms that can localize failures in the network even in the presence of uncertainty in the inferred dependencies between probes and network components. In this paper, we propose a fault diagnosis tool with following novel features: (1) We present an adaptive probing based solution for fault diagnosis which is cost-effective, failure resistant, more accurate, and involves less management traffic as compared to the preplanned probing approach. (2) We address the issues that arise with the presence of a non-deterministic environment and present probing algorithms that consider the involved uncertainties in the collected network information.
Prepared through collaborative participation in the Communications and Networks Consortium sponsored by the U.S. Army Research Laboratory under the Collaborative Technology Alliance Program, Cooperative Agreement DAAD19-01-2-0011. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation thereon.
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Bejerano, Y., Rastogi, R.: Robust monitoring of link delays and faults in IP networks. In: IEEE INFOCOM, San Francisco, CA (March 2003)
Brodie, M., Rish, I., Ma, S.: Optimizing probe selection for fault localization. In: Distributed Systems Operations Management, pp. 1147–1157 (2001)
Downey, A.B.: Using pathchar to estimate Internet link characteristics. In: ACM SIGCOMM, Cambridge, MA (1999)
Huffaker, B., Plummer, D., Moore, D., Claffy, K.: Topology discovery by active probing. In: Symposium on Applications and the Internet, Nara, Japan (January 2002)
Lai, K., Baker, M.: Measuring bandwidth. In: IEEE INFOCOM 1999, New York City (March 1999)
Li, F., Thottan, M.: End-to-end service quality measurement using source-routed probes. In: 25th Annual IEEE Conference on Computer Communications (INFOCOM), Barcelona, Spain (April 2006)
Natu, M., Sethi, A.S.: Adaptive fault localization in mobile ad-hoc battlefield networks. In: MILCOM 2005, Atlantic City, NJ (2005)
Natu, M., Sethi, A.S.: Active probing approach for fault localization in computer networks. In: E2EMON 2006, Vancouver, Canada (2006)
Natu, M., Sethi, A.S.: Efficient probing techniques for fault diagnosis. In: ICIMP 2007. International Conference on Internet Monitoring and Protection, Silicon Valley, CA (to appear, 2007)
Rish, I., Brodie, M., Ma, S., Odintsova, N., Beygelzimer, A., Grabarnik, G., Hernandez, K.: Adaptive diagnosis in distributed systems. IEEE Transactions on Neural Networks 6(5), 1088–1109 (2005)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 IFIP International Federation for Information Processing
About this paper
Cite this paper
Natu, M., Sethi, A.S. (2007). Probabilistic Fault Diagnosis Using Adaptive Probing. In: Clemm, A., Granville, L.Z., Stadler, R. (eds) Managing Virtualization of Networks and Services. DSOM 2007. Lecture Notes in Computer Science, vol 4785. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75694-1_4
Download citation
DOI: https://doi.org/10.1007/978-3-540-75694-1_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-75693-4
Online ISBN: 978-3-540-75694-1
eBook Packages: Computer ScienceComputer Science (R0)