| Presentation | 2018-11-16 Prediction of Variation in Network Traffic by RNN Haruka Osanai, Akihiro Nakao, Shu Yamamoto, Saneyasu Yamaguchi, Masato Oguchi, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | A network congestion is caused by large scale disasters, multiple OSes upgrades which happen simultaneously, DDoS attack, and so on. When the network congestion happens, it is difficult to deal with. Therefore, predicting when it happens and preventing it is important. It is expected to detect congestion state by Deep Learning in advance and deal with it effectively. We propose a way to analyze a change of network traffic and study congestion state by RNN in this paper. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Deep Learning / RNN / Network traffic / Variation Prediction |
| Paper # | NS2018-145 |
| Date of Issue | 2018-11-08 (NS) |
| Conference Information | |
| Committee | CQ / ICM / NS |
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| Conference Date | 2018/11/15(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | Takanori Hayashi(Hiroshima Inst. of Tech.) / Kiyohito Yoshihara(KDDI Research) / Yoshikatsu Okazaki(NTT) |
| Vice Chair | Hideyuki Shimonishi(NEC) / Jun Okamoto(NTT) / Yoichi Yamashita(NTT-N) / Takumi Miyoshi(Shibaura Inst. of Tech.) / Akihiro Nakao(Univ. of Tokyo) |
| Secretary | Hideyuki Shimonishi(NTT) / Jun Okamoto(Nippon Inst. of Tech.) / Yoichi Yamashita(KDDI Research) / Takumi Miyoshi(NTT) / Akihiro Nakao(NTT) |
| Assistant | Chikara Sasaki(KDDI Research) / Yoshiaki Nishikawa(NEC) / Ryo Yamamoto(UEC) / Yunchen Zhu(Hitachi) / Kenichi Kashibuchi(NTT) |
| Paper Information | |
| Registration To | Technical Committee on Communication Quality / Technical Committee on Information and Communication Management / Technical Committee on Network Systems |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Prediction of Variation in Network Traffic by RNN |
| Sub Title (in English) | |
| Keyword(1) | Deep Learning |
| Keyword(2) | RNN |
| Keyword(3) | Network traffic |
| Keyword(4) | Variation Prediction |
| 1st Author's Name | Haruka Osanai |
| 1st Author's Affiliation | Ochanomizu University(Ochanomizu Univ.) |
| 2nd Author's Name | Akihiro Nakao |
| 2nd Author's Affiliation | the University of Tokyo(Univ. of Tokyo) |
| 3rd Author's Name | Shu Yamamoto |
| 3rd Author's Affiliation | the University of Tokyo(Univ. of Tokyo) |
| 4th Author's Name | Saneyasu Yamaguchi |
| 4th Author's Affiliation | Kogakuin University(Kogakuin Univ.) |
| 5th Author's Name | Masato Oguchi |
| 5th Author's Affiliation | Ochanomizu University(Ochanomizu Univ.) |
| Date | 2018-11-16 |
| Paper # | NS2018-145 |
| Volume (vol) | vol.118 |
| Number (no) | NS-301 |
| Page | pp.pp.87-92(NS), |
| #Pages | 6 |
| Date of Issue | 2018-11-08 (NS) |