Point of reference in perception of network performance by active probing

Myrvin Yap, Marat Zhanikeev, Yoshiaki Tanaka

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    Reliability of active measurement results is an omnipresent issue in all existing measurement tools. Till this day, no reference point exists that would enable to compare measurement methods in efficiency and reliability. Partially, this is due to inability to attribute any particular probability model to both probing results as well as to the traffic probes interfere with. This paper proposed to analyze spectrum of measurement results in search for a reliable reference point. It is discovered that spectrum distribution of probing results are linearly dependent to linear changes in traffic.

    Original languageEnglish
    Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Pages205-214
    Number of pages10
    Volume4773 LNCS
    Publication statusPublished - 2007
    Event10th Asia-Pacific Network Operations and Management Symposium, APNOMS 2007 - Sapporo
    Duration: 2007 Oct 102007 Oct 12

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume4773 LNCS
    ISSN (Print)03029743
    ISSN (Electronic)16113349

    Other

    Other10th Asia-Pacific Network Operations and Management Symposium, APNOMS 2007
    CitySapporo
    Period07/10/1007/10/12

    Fingerprint

    Network Performance
    Network performance
    Spectrum Analysis
    Reference Point
    Traffic
    Probability Model
    Probe
    Linearly
    Attribute
    Perception
    Dependent

    ASJC Scopus subject areas

    • Computer Science(all)
    • Biochemistry, Genetics and Molecular Biology(all)
    • Theoretical Computer Science

    Cite this

    Yap, M., Zhanikeev, M., & Tanaka, Y. (2007). Point of reference in perception of network performance by active probing. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4773 LNCS, pp. 205-214). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4773 LNCS).

    Point of reference in perception of network performance by active probing. / Yap, Myrvin; Zhanikeev, Marat; Tanaka, Yoshiaki.

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4773 LNCS 2007. p. 205-214 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4773 LNCS).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Yap, M, Zhanikeev, M & Tanaka, Y 2007, Point of reference in perception of network performance by active probing. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 4773 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4773 LNCS, pp. 205-214, 10th Asia-Pacific Network Operations and Management Symposium, APNOMS 2007, Sapporo, 07/10/10.
    Yap M, Zhanikeev M, Tanaka Y. Point of reference in perception of network performance by active probing. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4773 LNCS. 2007. p. 205-214. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
    Yap, Myrvin ; Zhanikeev, Marat ; Tanaka, Yoshiaki. / Point of reference in perception of network performance by active probing. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4773 LNCS 2007. pp. 205-214 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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