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 journalArticlepeer-review

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

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

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