Presentation 2003/12/4
Traffic Data Analysis Based on Extreme Value Theory and Its Accuracy
Masato UCHIDA,
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Abstract(in English) The behavior of the tail distributions of the variables concerning teletraffic states, such as packet loss rate, throughput, link-usage rate, delay time, and queue length, greatly influences the communication quality, application performance, and network design, etc. Against this background, this paper analyzes the teletraffic data taking extreme values which is important for the appropriate management and operation of telecommunication services. For the analysis of such data, this paper uses Extreme Value Theory (EVT), which provides a firm theoretical foundation on which we can build statistical models that describe extreme events. The analyzed results show that the the estimated distribution based on EVT by using limited known teletraffic data can approximate the tail distribution of unknown data, though the histgram constructed by using same limited known teletraffic data can not approximate the tail distribution of the unknown data.
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Keyword(in English) Extreme Value Theory / Tail Distribution / Known Data / Unknown Data
Paper # IN2003-135
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Conference Date 2003/12/4(1days)
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Title (in Japanese) (See Japanese page)
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Title (in English) Traffic Data Analysis Based on Extreme Value Theory and Its Accuracy
Sub Title (in English)
Keyword(1) Extreme Value Theory
Keyword(2) Tail Distribution
Keyword(3) Known Data
Keyword(4) Unknown Data
1st Author's Name Masato UCHIDA
1st Author's Affiliation NTT Service Integration Laboratories, NTT Corporation()
Date 2003/12/4
Paper # IN2003-135
Volume (vol) vol.103
Number (no) 492
Page pp.pp.-
#Pages 6
Date of Issue