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

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

研究成果: Article査読

1 被引用数 (Scopus)

抄録

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.

本文言語English
ページ(範囲)413-420
ページ数8
ジャーナルIEICE Transactions on Communications
E87-B
3
出版ステータスPublished - 2004 3

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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