| Presentation | 2022-08-05 Machine Learning-Based Network Traffic Prediction with Tunable Parameters Kaito Kuriyama, Kohei Watabe, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Network evaluation has become increasingly important in recent years. Network evaluation requires large amounts of traffic data. Recent studies have focused on generative models using machine learning. However, few generative models exist for traffic. In this paper, we propose a traffic model using machine learning. Comparative evaluation with a conventional model using actual traffic traces shows that it is more reproducible than the conventional model. Furthermore, we showed that the traffic characteristics can be arbitrarily adjusted. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Time series generation / GAN / LSTM / Network traffic / Generative model |
| Paper # | IN2022-20 |
| Date of Issue | 2022-07-28 (IN) |
| Conference Information | |
| Committee | IN / CCS |
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| Conference Date | 2022/8/4(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Hokkaido University(Centennial Hall) |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Network Science, Future Network, Cloud/SDN/Virtualization, Contents Delivery/Contents Exchange, and others |
| Chair | Kunio Hato(Internet Multifeed) / Megumi Akai(Hokkaido Univ.) |
| Vice Chair | Tsutomu Murase(Nagoya Univ.) / Hidehiro Nakano(Tokyo City Univ.) / Masaki Aida(TMU) |
| Secretary | Tsutomu Murase(KDDI Research) / Hidehiro Nakano(Nagaoka Univ. of Tech.) / Masaki Aida(NTT) |
| Assistant | / Hiroyuki Yasuda(Univ. of Tokyo) / Hiroyasu Ando(Tsukuba Univ.) / Tomoyuki Sasaki(Shonan Inst. of Tech.) / Miki Kobayashi(Rissho Univ.) |
| Paper Information | |
| Registration To | Technical Committee on Information Networks / Technical Committee on Complex Communication Sciences |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Machine Learning-Based Network Traffic Prediction with Tunable Parameters |
| Sub Title (in English) | |
| Keyword(1) | Time series generation |
| Keyword(2) | GAN |
| Keyword(3) | LSTM |
| Keyword(4) | Network traffic |
| Keyword(5) | Generative model |
| 1st Author's Name | Kaito Kuriyama |
| 1st Author's Affiliation | Nagaoka University of Technology(Nagaoka Univ. of Tech.) |
| 2nd Author's Name | Kohei Watabe |
| 2nd Author's Affiliation | Nagaoka University of Technology(Nagaoka Univ. of Tech.) |
| Date | 2022-08-05 |
| Paper # | IN2022-20 |
| Volume (vol) | vol.122 |
| Number (no) | IN-146 |
| Page | pp.pp.27-32(IN), |
| #Pages | 6 |
| Date of Issue | 2022-07-28 (IN) |