Presentation | 1997/8/29 Chaotic maps for modeling self-similar traffic processes Naoki TANAKA, Hiroshi OKAMOTO, Masayoshi NAITO, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Recent statistical analyses of large set of traffic measurements in high-speed networks have provided convincing evidence for the presence of features in actual networks such as burstness, long-range dependence and selfsimilarity. In this report we demonstrate that these characteristics of the traffic can be modeled successfully by using a class of chaotic maps. We further study the models based on these chaotic maps for simple traffic processes, and show the effectiveness of the models. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | traffic processes / self-similarity / chaotic maps / intermittency / long-range dependence |
Paper # | SSE97-68 |
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Committee | SSE |
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Conference Date | 1997/8/29(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Switching Systems Engineering (SSE) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Chaotic maps for modeling self-similar traffic processes |
Sub Title (in English) | |
Keyword(1) | traffic processes |
Keyword(2) | self-similarity |
Keyword(3) | chaotic maps |
Keyword(4) | intermittency |
Keyword(5) | long-range dependence |
1st Author's Name | Naoki TANAKA |
1st Author's Affiliation | Advanced Research Laboratory, Hitachi, Ltd.() |
2nd Author's Name | Hiroshi OKAMOTO |
2nd Author's Affiliation | Advanced Research Laboratory, Hitachi, Ltd. |
3rd Author's Name | Masayoshi NAITO |
3rd Author's Affiliation | Advanced Research Laboratory, Hitachi, Ltd. |
Date | 1997/8/29 |
Paper # | SSE97-68 |
Volume (vol) | vol.97 |
Number (no) | 242 |
Page | pp.pp.- |
#Pages | 6 |
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