Quantitative analysis of temporal patterns in loosely coupled active measurement results

Marat Zhanikeev*, Yoshiaki Tanaka

*この研究の対応する著者

研究成果: Conference contribution

抄録

With constantly increasing complexity of active measurement methods, the issue of processing measurement results becomes important. Similarly to traditional pattern discovery, temporal patterns found in active measurement samples should be provided effective storage and means to compare to other samples. Traditional time series data mining is not applicable to temporal patterns in active measurement time series. This paper proposes a pattern discovery method based on unique features of active measurement results. The method is implemented in form of a database and is used in the paper to verify the proposed method.

本文言語English
ホスト出版物のタイトルManaging Next Generation Networks and Services - 10th Asia-Pacific Network Operations and Management Symposium, APNOMS 2007, Proceedings
ページ415-424
ページ数10
出版ステータスPublished - 2007 12月 1
イベント10th Asia-Pacific Network Operations and Management Symposium, APNOMS 2007 - Sapporo, Japan
継続期間: 2007 10月 102007 10月 12

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
4773 LNCS
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Conference

Conference10th Asia-Pacific Network Operations and Management Symposium, APNOMS 2007
国/地域Japan
CitySapporo
Period07/10/1007/10/12

ASJC Scopus subject areas

  • 理論的コンピュータサイエンス
  • コンピュータ サイエンス(全般)

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