• DocumentCode
    2323819
  • Title

    Prediction of performance degradation in telecommunication networks using Joint Clustering and association analysis techniques

  • Author

    Al-Fuqaha, A. ; Rayes, A. ; Kountanis, D. ; Abed, H. ; Kamel, A. ; Salih, R.

  • Author_Institution
    Comput. Sci. Dept., Western Michigan Univ., Kalamazoo, MI, USA
  • fYear
    2010
  • fDate
    6-10 Dec. 2010
  • Firstpage
    534
  • Lastpage
    538
  • Abstract
    One of the significant problems that high-tech companies are facing is the management and monitoring of networks in order to provide better and more reliable services for their customers. This paper introduces a new approach for the prediction of network failure and performance degradation using Joint Clustering and Association Analysis approach (JCAA). JCAA differs from existing prediction techniques in terms of exploiting the clustering and association analysis techniques in order to improve the quality of prediction. The role of clustering is to classify the input data into groups of k-means clusters, while the association analysis technique discovers the causal relationships between the groups. The experimental results demonstrate that the proposed system is truly effective in enhancing the quality of prediction.
  • Keywords
    telecommunication network management; telecommunication network reliability; joint clustering and association analysis approach; network failure prediction; performance degradation; telecommunication networks; autonomic network management; failure prediction; joint clustering and association analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    GLOBECOM Workshops (GC Wkshps), 2010 IEEE
  • Conference_Location
    Miami, FL
  • Print_ISBN
    978-1-4244-8863-6
  • Type

    conf

  • DOI
    10.1109/GLOCOMW.2010.5700377
  • Filename
    5700377