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A Resource Allocating Neural Network Based Approach for Detecting End-to-End Network Performance Anomaly

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Advances in Neural Networks - ISNN 2006 (ISNN 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3973))

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Abstract

Automatic detection of end-to-end network performance anomalies is important to efficient network management and optimization. We present an end-to-end network performance anomalies detection method, based on characterizing of the dynamic statistical properties of RTT normality. The experiment on real Internet end-to-end path RTT data shows that, the proposed method is accurate in detecting performance anomalies, it can successfully detect about 96.25% anomalies in the experiment.

This work was supported by National Natural Science Foundation of China under grant 60273070, 60473031 and 60403031, the National High-Technology Program of China (863) under grant 2005AA121560, the Hunan Provincial Natural Science Foundation of China under grant 05JJ30116.

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Author information

Authors and Affiliations

  1. College of Computer and Communication, Hunan University, Changsha, 410082, China

    Wenwei Li

  2. School of Software, Hunan University, Changsha, 410082, China

    Dafang Zhang, Jinmin Yang & Lei Wang

  3. Institute of Computing Technology, Chinese Academy of Science, Beijing, 100080, China

    Gaogang Xie

Authors
  1. Wenwei Li
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  2. Dafang Zhang
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  3. Jinmin Yang
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  4. Gaogang Xie
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  5. Lei Wang
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Editor information

Editors and Affiliations

  1. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  2. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

  3. Department of Electrical Engineering, University of Louisville, 40292, Louisville, KY, U.S.A

    Jacek M. Zurada

  4. Laboratory for Computational Biology, Shanghai Center for Systems Biomedicine, 800 Dong Chuan Rd, 200240, Shanghai, China

    Bao-Liang Lu

  5. School of Electrical and Electronic Engineering, University of Manchester, UK

    Hujun Yin

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© 2006 Springer-Verlag Berlin Heidelberg

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Li, W., Zhang, D., Yang, J., Xie, G., Wang, L. (2006). A Resource Allocating Neural Network Based Approach for Detecting End-to-End Network Performance Anomaly. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3973. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760191_27

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  • DOI: https://doi.org/10.1007/11760191_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34482-7

  • Online ISBN: 978-3-540-34483-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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