Presentation 2003/1/30
Proposal and Evaluation of Packet Loss Rate Inference Scheme by using Packet Train Method for Active Measurement
Yoshiko MATSUMOTO, Kenji KAWAHARA, Yuji OIE,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) In recent years, the Internet has manifold traffic such as audio and video which require different QoS (Quality of Service). In the QoS aware Internet, performance measurement may become important technique to estimate network condition prior to data transmission and to confirm its quality. In the active measurement which is one of the measurement techniques, some observer sends probe packets, gets their performance such as packet loss, delay and/or throughput and infers some performance of the system without sending probe packets from them. Some amount of probe traffic is required to improve the accuracy of inference, however, this may disturb the status of the original system. Thus, in this paper, we will focus on the "packet train method" for sending probe packets, and new inference scheme in terms of packet loss rate by using the incremental behavior of loss rate of successive probe packets to moderate the inference of the disturbance with high precision. By modeling some router as simple Batch Geom/D/1 queueing system, we will theoretically and statistically analyze loss performance and investigate the effectiveness of the proposed scheme.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Active Measurement / Packet Train Method / Packet Loss Rate / Polynominal Regression
Paper # IN2002-188,IA2002-44
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Conference Information
Committee IA
Conference Date 2003/1/30(1days)
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Paper Information
Registration To Internet Architecture(IA)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Proposal and Evaluation of Packet Loss Rate Inference Scheme by using Packet Train Method for Active Measurement
Sub Title (in English)
Keyword(1) Active Measurement
Keyword(2) Packet Train Method
Keyword(3) Packet Loss Rate
Keyword(4) Polynominal Regression
1st Author's Name Yoshiko MATSUMOTO
1st Author's Affiliation Department of Computer Science and Electronics,Kyusyu Institute of Technology()
2nd Author's Name Kenji KAWAHARA
2nd Author's Affiliation Department of Computer Science and Electronics,Kyusyu Institute of Technology
3rd Author's Name Yuji OIE
3rd Author's Affiliation Department of Computer Science and Electronics,Kyusyu Institute of Technology
Date 2003/1/30
Paper # IN2002-188,IA2002-44
Volume (vol) vol.102
Number (no) 635
Page pp.pp.-
#Pages 6
Date of Issue