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International Conference on Algorithms and Architectures for Parallel Processing

ICA3PP 2018: Algorithms and Architectures for Parallel Processing pp 59–71Cite as

An Approach of Collecting Performance Anomaly Dataset for NFV Infrastructure

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11336))

Abstract

Network Function Virtualization (NFV) technology is widely used in industry and academia. Meanwhile, it brings a lot of challenges to the NFV applications’ reliability, such as anomaly detection, anomaly location, anomaly prediction and so on. All of these studies need a large number of anomaly data information. This paper designs a method for collecting anomaly data from Infrastructure as a Service (IaaS), and constructs an anomaly database for NFV applications. Three types of anomaly datasets are created for anomaly study, including datasets of workload with performance data, fault-load with performance data and violation of Service Level Agreement (SLA) with performance. In order to simulate an anomaly in a production environment better, we use Kubernetes to build a distributed environment, and to accelerate the occurrence of anomalies, a fault injection system is utilized. Our aim is to provide more valuable anomaly data for reliability research in NFV environments.

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Notes

  1. 1.

    http://kdd.ics.uci.edu/databases/kddcup99/kddcup99.html.

  2. 2.

    https://github.com/numenta/NAB.

  3. 3.

    https://webscope.sandbox.yahoo.com/catalog.php?datatype=s.

  4. 4.

    https://en.wikipedia.org/wiki/Service-level_agreement.

  5. 5.

    http://www.projectclearwater.org/.

  6. 6.

    https://github.com/XLab-Tongji.

  7. 7.

    https://www.zabbix.com/.

  8. 8.

    https://www.nagios.org/.

  9. 9.

    https://www.cacti.net/.

  10. 10.

    https://rancher.com/.

  11. 11.

    https://clearwater.readthedocs.io/en/stable/Clearwater_stres_testing.html.

  12. 12.

    https://github.com/XLab-Tongji/ADNFVI.

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Author information

Authors and Affiliations

  1. School of Software Engineering, Tongji University, Shanghai, China

    Qingfeng Du, Yu He, Tiandi Xie, Kanglin Yin & Juan Qiu

  2. Software Engineering R&D Centre, Tongji University, Jishi Building, Shanghai, China

    Qingfeng Du, Yu He, Tiandi Xie, Kanglin Yin & Juan Qiu

Authors
  1. Qingfeng Du
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  2. Yu He
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  3. Tiandi Xie
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  4. Kanglin Yin
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  5. Juan Qiu
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Corresponding author

Correspondence to Yu He .

Editor information

Editors and Affiliations

  1. Rutgers University–Newark, Newark, NJ, USA

    Jaideep Vaidya

  2. Guangzhou University, Guangzhou, China

    Jin Li

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Du, Q., He, Y., Xie, T., Yin, K., Qiu, J. (2018). An Approach of Collecting Performance Anomaly Dataset for NFV Infrastructure. In: Vaidya, J., Li, J. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2018. Lecture Notes in Computer Science(), vol 11336. Springer, Cham. https://doi.org/10.1007/978-3-030-05057-3_5

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  • DOI: https://doi.org/10.1007/978-3-030-05057-3_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-05056-6

  • Online ISBN: 978-3-030-05057-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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