Institutional Repository of Computer Application Research Laboratory
| Investigation of Traffic Classification Applied to an Astronomical Data Transmission Network of the XAO Using Deep Learning | |
Wang,Jie1,2 ; Zhang,Hai-Long1,2,3; Wang,Na1,3; Ye,Xin-Chen1,2; Wang,Wan-Qiong1; Li,Jia1; Zhang,Meng1,4; Zhang,Ya-Zhou1,4; Du,Xu1,4
| |
| 2023-02-10 | |
| Source Publication | Research in Astronomy and Astrophysics
 |
| ISSN | 1674-4527 |
| Volume | 23Issue:3Pages:035003 |
| Contribution Rank | 1 |
| Abstract | Abstract A telecommunication network used for the transmission of astronomical observation data, telescope remote control and other astronomical research purposes is a critical infrastructure. The monitoring and analysis of network traffic, which help improve the network performance and the utilization of network resources, are a challenging task. The accurate identification of the astronomical data traffic will effectively improve transmission efficiency. In this paper, a classification method applied to types of traffic containing astronomical data using deep learning is proposed. The advantages of a convolutional neural network model in image classification are exploited to classify types of traffic containing astronomical data. The objective is to identify the mixed traffic in the network and accurately identify types of traffic containing astronomical data. The effectiveness of the model in improving classification accuracy is also discussed. Actual traffic data captured by Tcpdump and Wireshark are tested, and the experimental results indicate that the proposed method can accurately classify types of traffic containing astronomical data. |
| Keyword | astronomical databases: miscellaneous virtual observatory tools surveys |
| DOI | 10.1088/1674-4527/acafc5 |
| Indexed By | SCI |
| Language | 英语 |
| WOS ID | WOS:000936425200001 |
| CSCD ID | CSCD:7437937 |
| Publisher | National Astromonical Observatories, CAS and IOP Publishing |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.xao.ac.cn/handle/45760611-7/6258 |
| Collection | 计算机技术应用研究室 110米口径全可动射电望远镜（QTT）_技术成果 科研仪器设备产出_利用南山1米大视场望远镜（NOWT）观测数据的文章 |
| Corresponding Author | Wang,Jie; Zhang,Hai-Long |
| Affiliation | 1.Xinjiang Astronomical Observatory, Chinese Academy of Sciences, Urumqi 830011, China; wangjie@xao.ac.cn, zhanghailong@xao.ac.cn 2.National Astronomical Data Center, Beijing 100101, China 3.Key Laboratory of Radio Astronomy, Chinese Academy of Sciences, Nanjing 210008, China 4.University of Chinese Academy of Sciences, Beijing 100049, China |
| First Author Affilication | Xinjiang Astronomical Observatory, Chinese Academy of Sciences |
| Corresponding Author Affilication | Xinjiang Astronomical Observatory, Chinese Academy of Sciences |
| Recommended Citation GB/T 7714 | Wang,Jie,Zhang,Hai-Long,Wang,Na,et al. Investigation of Traffic Classification Applied to an Astronomical Data Transmission Network of the XAO Using Deep Learning[J]. Research in Astronomy and Astrophysics,2023,23(3):035003. |
| APA | Wang,Jie.,Zhang,Hai-Long.,Wang,Na.,Ye,Xin-Chen.,Wang,Wan-Qiong.,...&Du,Xu.(2023).Investigation of Traffic Classification Applied to an Astronomical Data Transmission Network of the XAO Using Deep Learning.Research in Astronomy and Astrophysics,23(3),035003. |
| MLA | Wang,Jie,et al."Investigation of Traffic Classification Applied to an Astronomical Data Transmission Network of the XAO Using Deep Learning".Research in Astronomy and Astrophysics 23.3(2023):035003. |
| Files in This Item: | ||||||
| File Name/Size | DocType | Version | Access | License | ||
| Wang-2023-Investigat（1591KB） | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | View Application Full Text | |
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.
Edit Comment