DCAA: A Dynamic Constrained Adaptive Aggregation Method for Effective Network Traffic Information Summarization

Kazuhide Koide, Glenn Mansfield Keeni, Gen Kitagata, Norio Shiratori

    Research output: Contribution to journalArticle

    1 Citation (Scopus)

    Abstract

    Online and realtime traffic summarization is a challenge as, except for the routine cases, aggregation parameters or, the flows that need to be observed are not known a priori. Dynamic adaptive aggregation algorithms adapt to the network traffic to detect the important flows. But present day algorithms are inadequate as they often produce inaccurate or meaningless aggregates. In this work we propose a Dynamic Constrained Adaptive Aggregation algorithm that does not produce the meaningless aggregates by using information about the network's configuration. We compare the performance of this algorithm with the erstwhile Dynamic (Unconstrained) Adaptive Aggregation algorithm and show its efficacy. Further we use the network map context that shows the network flows in an intuitive manner. Several applications of the algorithm and network map based visualization are discussed.

    Original languageEnglish
    Pages (from-to)413-420
    Number of pages8
    JournalIEICE Transactions on Communications
    VolumeE87-B
    Issue number3
    Publication statusPublished - 2004 Mar

    Keywords

    • Adaptability
    • Correctness
    • DCAA
    • Network map
    • Traffic summarization

    ASJC Scopus subject areas

    • Electrical and Electronic Engineering
    • Computer Networks and Communications

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