fast fourier transform based ip traffic classification system for sipto at h(e)nb
文献类型：会议论文
| 作者 | Han Lin ; Huang Liusheng ; Hu Qian ; Han Xue ; Shi Jinglin |
| 出版日期 | 2012 |
| 会议名称 | 2012 7th International ICST Conference on Communications and Networking in China, CHINACOM 2012 |
| 会议日期 | August 7, 2012 - August 10, 2012 |
| 会议地点 | Kun Ming, China |
| 关键词 | Computer simulation Ethers Fast Fourier transforms Learning algorithms Mobile telecommunication systems |
| 页码 | 430-435 |
| 中文摘要 | 3GPP has recently introduced LIPA(Local IP Access) and SIPTO(Selected IP Traffic Offload) to offload traffic from the core network, which brings new challenge to on-line traffic classification, because of the large amount of data and the difference of mobile network from wired network, such as high bit error rates(BER) and temporary disconnections. Therefore, other proposed schemes which aim at ether LIPA at H(e)NB or SIPTO at macro network could not get high accuracy and high speed at the same time, and traffic classification methodologies in wired IP network are not applicable. This paper proposes a fast fourier transform(FFT) based IP traffic classification system for SIPTO at H(e)NB, which focuses on classifying each packet at H(e)NB by extracting the application layer payload pattern using FFT. Pattern extraction and classification using machine learning algorithms are simulated, and results show that our system outperforms existing methods by offering about 3%-6% improvement in classification accuracy with about 7% time. Simulation of SIPTO shows good reduction of press to the core network and low false rates. © 2012 IEEE. |
| 英文摘要 | 3GPP has recently introduced LIPA(Local IP Access) and SIPTO(Selected IP Traffic Offload) to offload traffic from the core network, which brings new challenge to on-line traffic classification, because of the large amount of data and the difference of mobile network from wired network, such as high bit error rates(BER) and temporary disconnections. Therefore, other proposed schemes which aim at ether LIPA at H(e)NB or SIPTO at macro network could not get high accuracy and high speed at the same time, and traffic classification methodologies in wired IP network are not applicable. This paper proposes a fast fourier transform(FFT) based IP traffic classification system for SIPTO at H(e)NB, which focuses on classifying each packet at H(e)NB by extracting the application layer payload pattern using FFT. Pattern extraction and classification using machine learning algorithms are simulated, and results show that our system outperforms existing methods by offering about 3%-6% improvement in classification accuracy with about 7% time. Simulation of SIPTO shows good reduction of press to the core network and low false rates. © 2012 IEEE. |
| 收录类别 | EI |
| 会议主办者 | EAI; IEEE Computer Society |
| 会议录 | 2012 7th International ICST Conference on Communications and Networking in China, CHINACOM 2012 - Proceedings
 |
| 语种 | 英语 |
| ISBN号 | 9781467326995 |
| 源URL | [http://ir.iscas.ac.cn/handle/311060/15945]  |
| 专题 | 软件研究所_软件所图书馆_会议论文 |
| 推荐引用方式 GB/T 7714 | Han Lin,Huang Liusheng,Hu Qian,et al. fast fourier transform based ip traffic classification system for sipto at h(e)nb[C]. 见:2012 7th International ICST Conference on Communications and Networking in China, CHINACOM 2012. Kun Ming, China. August 7, 2012 - August 10, 2012. |
入库方式： OAI收割
来源：软件研究所
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