| Presentation | 2009-05-21 Maximum Likelihood Link Loss Rate Inference with Network Coding Takahiro MATSUDA, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Network Tomography is an infering technique for internal network characteristics using end-to-end measurements. In this article, we propose a network tomography technique with network coding for inferring link loss rate. Network coding allows intermediate nodes in a network to mix packets into a single packet before forwarding them. Network coding has an advantage in terms of bandwidth usage when it is cooperated in network tomography, because it can reduces the number of outstanding packets for infering link loss rate. In this article, we propose a maximum likelihood inference method with network coding for link loss rate. The proposed method is based on the EM (Expectation Maximization) algorithm and infers link loss rate according to received packets, network topology, and coding information. We evaluate the proposed method in simple simulation scenarios. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Network Coding / Network Tomography / Link Loss Rate / Maximum Likelihood Inference / EM algorithm |
| Paper # | IN2009-1 |
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| Conference Information | |
| Committee | IN |
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| Conference Date | 2009/5/14(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
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| Paper Information | |
| 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) | Maximum Likelihood Link Loss Rate Inference with Network Coding |
| Sub Title (in English) | |
| Keyword(1) | Network Coding |
| Keyword(2) | Network Tomography |
| Keyword(3) | Link Loss Rate |
| Keyword(4) | Maximum Likelihood Inference |
| Keyword(5) | EM algorithm |
| 1st Author's Name | Takahiro MATSUDA |
| 1st Author's Affiliation | Graduate School of Engineering, Osaka University() |
| Date | 2009-05-21 |
| Paper # | IN2009-1 |
| Volume (vol) | vol.109 |
| Number (no) | 37 |
| Page | pp.pp.- |
| #Pages | 6 |
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