• DocumentCode
    2641266
  • Title

    Hierarchical summarization techniques for network traffic

  • Author

    Mahmood, A.N. ; Leckie, C. ; Islam, R. ; Tari, Z.

  • Author_Institution
    Sch. of Comput. Sci. & I.T., R. Melbourne Inst. of Technol. Univ., Melbourne, VIC, Australia
  • fYear
    2011
  • fDate
    21-23 June 2011
  • Firstpage
    2474
  • Lastpage
    2479
  • Abstract
    In today´s high speed networks it is becoming increasingly challenging for network managers to understand the nature of the traffic that is carried in their network. A major problem for traffic analysis in this context is how to extract a concise yet accurate summary of the relevant aggregate traffic flows that are present in network traces. In this paper, we present two summarization techniques to minimize the size of the traffic flow report that is generated by a hierarchical cluster analysis tool. By analyzing the accuracy and compaction gain of our approach on a standard benchmark dataset, we demonstrate that our approach achieves more accurate summaries than those of an existing tool that is based on frequent itemset mining.
  • Keywords
    Internet; data mining; pattern clustering; telecommunication traffic; frequent itemset mining; hierarchical cluster analysis; hierarchical summarization techniques; high speed networks; network traffic; traffic analysis; traffic flows; Aggregates; Artificial intelligence; Clustering algorithms; Compaction; IP networks; Peer to peer computing; Protocols; Cluster analysis; Internet management; Summarization; Traffic analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics and Applications (ICIEA), 2011 6th IEEE Conference on
  • Conference_Location
    Beijing
  • ISSN
    pending
  • Print_ISBN
    978-1-4244-8754-7
  • Electronic_ISBN
    pending
  • Type

    conf

  • DOI
    10.1109/ICIEA.2011.5976009
  • Filename
    5976009