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Fault Localization for Heterogeneous Networks Using Alarm Correlation on Consolidated Inventory Database

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Challenges for Next Generation Network Operations and Service Management (APNOMS 2008)

Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 5297))

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Abstract

Over the decades, various fault localization techniques are introduced for the surveillance of the modern complex communication networks. But most of them analyze the events with limited data of network equipment configuration and the topology among them. But the analysis of alarm correlation based on the detailed end-to-end network view point is necessary to improve the effect of fault localization technique on complicated telecommunication networks. For this purpose, the database which supports the alarm correlation should be the integrated one which contains the information of the network elements and their connections in detail. We propose fault localization method which covers complex networks, e.g., SDH networks, IP backbone networks, IP access domain networks, xDSL networks and etc. The technique utilizes the CID(Consolidated Inventory Database) and applies the root cause event extraction method instead of problem-symptom model. And the implementations of the proposed system will be described. Then we discuss the various applications of the fault localization results on CID.

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References

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© 2008 Springer-Verlag Berlin Heidelberg

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Kim, J., Yang, YM., Park, S., Lee, S., Chung, B. (2008). Fault Localization for Heterogeneous Networks Using Alarm Correlation on Consolidated Inventory Database. In: Ma, Y., Choi, D., Ata, S. (eds) Challenges for Next Generation Network Operations and Service Management. APNOMS 2008. Lecture Notes in Computer Science, vol 5297. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88623-5_9

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  • DOI: https://doi.org/10.1007/978-3-540-88623-5_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-88622-8

  • Online ISBN: 978-3-540-88623-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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