Presentation | 2009-06-12 Network Traffic Prediction for Network Quality Anomaly Detection by RTP Communication Monitoring Satoshi IKADA, Nobuyuki NAKAMURA, Yoshitaka HAMAGUCHI, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Recently, NGN have been expected to keep required QoS because their architecture equip QoS management and various QoS evaluation methods have proposed. However, such methods calculate end-to-end QoS of a flow practically, so that we cannot grasp where the cause of the problem exists on the networks even though QoS degradation is reported. Therefore it is necessary to develop yet another measure of network quality by monitoring network traffics. In this paper, we propose a network traffic prediction method for network quality anomaly detection on Next Generation Networks (NGN). We show that our prediction method using both wavelet transformation and neural networks in detail. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | network traffic prediction / neural network / wavelet analysis |
Paper # | IN2009-24 |
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Committee | IN |
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Conference Date | 2009/6/4(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) | Network Traffic Prediction for Network Quality Anomaly Detection by RTP Communication Monitoring |
Sub Title (in English) | |
Keyword(1) | network traffic prediction |
Keyword(2) | neural network |
Keyword(3) | wavelet analysis |
1st Author's Name | Satoshi IKADA |
1st Author's Affiliation | Corporate Research and Development Center, Oki Electric Industry Co., Ltd.() |
2nd Author's Name | Nobuyuki NAKAMURA |
2nd Author's Affiliation | Corporate Research and Development Center, Oki Electric Industry Co., Ltd. |
3rd Author's Name | Yoshitaka HAMAGUCHI |
3rd Author's Affiliation | Corporate Research and Development Center, Oki Electric Industry Co., Ltd. |
Date | 2009-06-12 |
Paper # | IN2009-24 |
Volume (vol) | vol.109 |
Number (no) | 79 |
Page | pp.pp.- |
#Pages | 6 |
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