• DocumentCode
    2856635
  • Title

    TroubleMiner: Mining network trouble tickets

  • Author

    Medem, Amelie ; Akodjenou, Marc-Ismael ; Teixeira, Renata

  • Author_Institution
    LIP6 Lab., UPMC Paris Universitas, Paris, France
  • fYear
    2009
  • fDate
    1-5 June 2009
  • Firstpage
    113
  • Lastpage
    119
  • Abstract
    Network operators often use a trouble ticket system to track all the steps of troubleshooting and maintenance activities. The history of trouble tickets carries valuable information for network management. Unfortunately, trouble tickets are not easy to mine, because they basically contain the human description of a problem in free text. Analyzing hundreds of trouble tickets by hand is too cumbersome; it is then important to have the support of some automatic mechanism. This paper proposes TroubleMiner, a mechanism based on document clustering techniques to automatically mine network trouble tickets. We show the utility and generality of TroubleMiner by applying it to thousands of trouble tickets from two research backbone networks. Network operators can apply TroubleMiner to trouble tickets from their network to analyze general trends in network incidents and maintenance activities. Researchers can use the insights from our characterization to decide which troubleshooting or maintenance techniques are most needed.
  • Keywords
    data mining; document handling; information networks; pattern clustering; TroubleMiner; backbone networks; document clustering techniques; maintenance activities; mining network trouble tickets; network incidents; network operators; problem human description; Clustering algorithms; Data mining; History; Humans; Information management; Laboratories; Mechanical factors; Network-on-a-chip; Scheduling; Spine;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Integrated Network Management-Workshops, 2009. IM '09. IFIP/IEEE International Symposium on
  • Conference_Location
    New York, NY
  • Print_ISBN
    978-1-4244-3923-2
  • Electronic_ISBN
    978-1-4244-3924-9
  • Type

    conf

  • DOI
    10.1109/INMW.2009.5195946
  • Filename
    5195946