Presentation | 2002/6/14 Inferring statistics of each flow from aggregated-flow measurement Masato TSURU, Tetsuya TAKINE, Yuji OIE, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | For a statistical perspective of global traffic flows on a large network, we have proposed a way to infer unobservable statistics of each flow from measurements of aggregated-flows (sums of flows), which are easily measured at some links (router interfaces) in the network. In this paper, to relax some limitations in the previous work, we discuss some improvement: i) determining minimum rates of flows, ii) indirectly inferring statistics of some flows from those of other flows, iii) rounding (quantization) by an adequate bin size, and show simulation results, which indicate effectiveness of our improvement. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Traffic flow / Statistical Inference / Network tomography |
Paper # | IN2002-28 |
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Committee | IN |
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Conference Date | 2002/6/14(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Information Networks (IN) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Inferring statistics of each flow from aggregated-flow measurement |
Sub Title (in English) | |
Keyword(1) | Traffic flow |
Keyword(2) | Statistical Inference |
Keyword(3) | Network tomography |
1st Author's Name | Masato TSURU |
1st Author's Affiliation | JGN project, Telecommunications Advancement Organization of Japan (TAO):Japan Telecom Information Service Co., Ltd.() |
2nd Author's Name | Tetsuya TAKINE |
2nd Author's Affiliation | Dept. of Applied Mathematics and Physics, Graduate School of Informatics, Kyoto University |
3rd Author's Name | Yuji OIE |
3rd Author's Affiliation | Dept. of Computer Science and Electronics, Kyushu Institute of Technology:JGN project, Telecommunications Advancement Organization of Japan (TAO) |
Date | 2002/6/14 |
Paper # | IN2002-28 |
Volume (vol) | vol.102 |
Number (no) | 132 |
Page | pp.pp.- |
#Pages | 5 |
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