• DocumentCode
    1781155
  • Title

    Multi-layer fault diagnosis method in the Network Virtualization Environment

  • Author

    Congxian Yan ; Ying Wang ; Xuesong Qiu ; Wenjing Li ; Lu Guan

  • Author_Institution
    State Key Lab. of Networking & Switching Technol., Beijing Univ. of Posts & Telecommun., Beijing, China
  • fYear
    2014
  • fDate
    17-19 Sept. 2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    The performance and reliability of services relies on the network virtualization environment´s capabilities to effectively detect and diagnose faults in both substrate and virtual network. However, Network Virtualization Environment (NVE) brings to fault diagnosis new challenges such as inaccessible substrate network information and multi-layer faults. To solve the above issues, a Multi-layer Fault Diagnosis Method (MFDM) is proposed. A layer-by-layer strategy is used to resolve the problem of inaccessible substrate network information. And a filtering algorithm is proposed to distinguish the multi-layer faults in the network virtualization environment. At last, a contribution-based hypothesis selection algorithm is proposed to infer the most possible faults. Simulations and experimental results show that MFDM has a higher performance in the accuracy ratio, false-positive ratio.
  • Keywords
    computer network reliability; fault diagnosis; virtualisation; filtering algorithm; hypothesis selection algorithm; layer-by-layer strategy; multilayer fault diagnosis method; network virtualization environment; service reliability; virtual network; Accuracy; Fault diagnosis; Filtering; Filtering algorithms; Network topology; Substrates; Virtualization; Bayesian network; fault diagnosis; network virtualization environment; uncertainty reasoning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Network Operations and Management Symposium (APNOMS), 2014 16th Asia-Pacific
  • Conference_Location
    Hsinchu
  • Type

    conf

  • DOI
    10.1109/APNOMS.2014.6996580
  • Filename
    6996580