2.845

2023影响因子

(CJCR)

  • 中文核心
  • EI
  • 中国科技核心
  • Scopus
  • CSCD
  • 英国科学文摘

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

数字孪生网络(DTN): 概念、架构及关键技术

孙滔 周铖 段晓东 陆璐 陈丹阳 杨红伟 朱艳宏 刘超 李琴 王晓 沈震 瞿逢重 蒋怀光 王飞跃

孙滔, 周铖, 段晓东, 陆璐, 陈丹阳, 杨红伟, 朱艳宏, 刘超, 李琴, 王晓, 沈震, 瞿逢重, 蒋怀光, 王飞跃. 数字孪生网络(DTN): 概念、架构及关键技术. 自动化学报, 2021, 47(3): 569−582 doi: 10.16383/j.aas.c210097
引用本文: 孙滔, 周铖, 段晓东, 陆璐, 陈丹阳, 杨红伟, 朱艳宏, 刘超, 李琴, 王晓, 沈震, 瞿逢重, 蒋怀光, 王飞跃. 数字孪生网络(DTN): 概念、架构及关键技术. 自动化学报, 2021, 47(3): 569−582 doi: 10.16383/j.aas.c210097
Sun Tao, Zhou Cheng, Duan Xiao-Dong, Lu Lu, Chen Dan-Yang, Yang Hong-Wei, Zhu Yan-Hong, Liu Chao, Li Qin, Wang Xiao, Shen Zhen, Qu Feng-Zhong, Jiang Huai-Guang, Wang Fei-Yue. Digital twin network (DTN): concepts, architecture, and key technologies. Acta Automatica Sinica, 2021, 47(3): 569−582 doi: 10.16383/j.aas.c210097
Citation: Sun Tao, Zhou Cheng, Duan Xiao-Dong, Lu Lu, Chen Dan-Yang, Yang Hong-Wei, Zhu Yan-Hong, Liu Chao, Li Qin, Wang Xiao, Shen Zhen, Qu Feng-Zhong, Jiang Huai-Guang, Wang Fei-Yue. Digital twin network (DTN): concepts, architecture, and key technologies. Acta Automatica Sinica, 2021, 47(3): 569−582 doi: 10.16383/j.aas.c210097

数字孪生网络(DTN): 概念、架构及关键技术

doi: 10.16383/j.aas.c210097
基金项目: 国家重点研发计划(2020YFB1806801, 2020YFB1806800), 国家自然科学基金资助(61773382)
详细信息
    作者简介:

    孙滔:中国移动通信有限公司研究院主任研究员, 网络创新实验室技术经理. 2008年获清华大学控制科学与工程博士学位. 主要研究方向移动网新架构, 网络智能化. E-mail: suntao@chinamobile.com

    周铖:中国移动通信有限公司研究院项目经理. 2004年获得北京交通大学信号与信息处理硕士学位. 主要研究方向为IP网络技术和网络智能化. E-mail: zhouchengyjy@chinamobile.com

    段晓东:中国移动通信有限公司研究院副院长. 南京邮电大学计算机科学与技术硕士学位. IMT-2030 (6G) 推进组网络技术组组长. 主要研究方向为5G/6G网络架构, 云计算及虚拟化, IP新技术. 本文通信作者. E-mail: duanxiaodong@chinamobile.com

    陆璐:中国移动通信有限公司研究院网络与IT技术研究所副所长. 北京邮电大学硕士学位. CCSA TC5核心网组组长. 主要研究方向为移动核心网, 未来网络架构, 边缘计算. E-mail: lulu@chinamobile.com

    陈丹阳:中国移动通信有限公司研究院研究员. 2020年获得西安电子科技大学通信与信息系统硕士学位. 主要研究方向为数字孪生网络和意图网络. E-mail: chendanyang@chinamobile.com

    杨红伟:中国移动通信有限公司研究院项目经理. 主要研究方向为网络智能化、网络性能测量. E-mail: yanghongwei@chinamobile.com

    朱艳宏:中国移动通信有限公司研究院算法模型研究员. 2018年获得北京邮电大学电子与通信工程硕士学位. 主要研究方向为网络智能化, 6G新技术. E-mail: zhuyanhong@chinamobile.com

    刘超:中国移动通信有限公司研究院核心网研究员. 从事TD-LTE、NBIOT、5G核心网等领域的技术攻关、研究和标准化工作十余年. E-mail: liuchaoyjy@chinamobile.com

    李琴:中国移动通信有限公司研究院研究员. 长期从事核心网、内容网络的技术和应用研究. 主要研究方向为网络智能化. E-mail: liqinyjy@chinamobile.com

    王晓:中国科学院自动化研究所复杂系统管理与控制国家重点实验室副研究员. 2016 年获得中国科学院大学社会计算博士学位. 主要研究方向为社会交通, 动态网群组织, 人工智能和社交网络分析. E-mail: x.wang@ia.ac.cn

    沈震:中国科学院自动化研究所副研究员. 主要研究方向为复杂系统, 智能制造. E-mail: zhen.shen@ia.ac.cn

    瞿逢重:浙江大学海洋学院教授, 海洋传感与网络研究所所长. 主要研究方向为水声通信与网, 信号处理. E-mail: jimqufz@zju.edu.cn

    蒋怀光:美国国家可再生能源实验室研究员. 主要研究方向为人工智能, 优化控制, 无人自动化系统, 能源系统. E-mail: Huaiguang.jiang@nrel.gov

    王飞跃:中国科学院自动化研究所研究员, 复杂系统管理与控制国家重点实验室主任, 中国科学院大学中国经济与社会安全研究中心主任, 青岛智能产业技术研究院院长. 主要研究方向为平行系统的方法与应用, 社会计算, 平行智能以及知识自动化. E-mail: feiyue.wang@ia.ac.cn

Digital Twin Network (DTN): Concepts, Architecture, and Key Technologies

Funds: Supported by National Key Research and Development Program of China (2020YFB1806801, 2020YFB1806800) and National Natural Science Foundation of China (61773382)
More Information
    Author Bio:

    SUN Tao Principal researcher of China Mobile Research Institute, director of the Network Innovation Laboratory. He received his Ph.D. degree in control science and engineering from Tsinghua University in 2008. His research interest covers new mobile network architectures and AI enabled networks

    ZHOU Cheng Project manager at China Mobile Research Institute. He received his master degree in signal and information processing from Beijing Jiaotong University in 2004. His research interest covers IP network technology and AI enabled networks

    DUAN Xiao-Dong Vice president of China Mobile Research Institute, and leader of the Network Technology Group of IMT-2030 (6G). He received his master degree in computer science from Nanjing University of Posts and Telecommunications. His research interest covers 5G/6G network architecture, cloud computing and virtualization, and new IP technology. Corresponding author of this paper

    LU Lu Deputy director of the Department of Network and IT Technology, China Mobile Research Institute; leader of the Core Network Group of CCSA TC5. She received her master degree from Beijing University of Posts and Telecommunications. Her research interest covers mobile core network, future network architecture, and edge computing

    CHEN Dan-Yang Researcher at China Mobile Research Institute. She received her master degree in communication and information system from Xidian University in 2020. Her research interest covers digital twin network and intent based network

    YANG Hong-Wei Project manager at China Mobile Research Institute. His research interest covers network intelligence and network performance measurement

    ZHU Yan-Hong Researcher at China Mobile Research Institute. She received her master degree in information and communication engineering from Beijing University of Posts and Telecommunications in 2018. Her research interests covers intelligence network and 6G

    LIU Chao Core network engineer at China Mobile Research Institute. He has been engaged in technical research and standardization in the fields of TD-LTE, NB-IOT, and 5G core networks more than 10 years

    LI Qin Researcher at China Mobile Research Institute. She has engaged in technical and application research on core network and content network for more than 10 years. Her main research interest is network intelligence

    WANG Xiao Associate professor at the State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences. She received her Ph.D. degree in social computing from University of Chinese Academy of Sciences, in 2016. Her research interest covers social transportation, cyber movement organizations, artificial intelligence, and social network analysis

    SHEN Zhen Associate professor at the Institute of Automation, Chinese Academy of Sciences. His research interest covers complex systems and intelligent manufacturing

    QU Feng-Zhong Professor at the Ocean College of Zhejiang University, and the chair of the Institute of Ocean Sensing and Networking, Zhejiang University. His research interest covers underwater acoustic communications and networking

    JIANG Huai-Guang Research leader at the National Renewable Energy Laboratory, USA. His research interest covers artificial intelligence, optimization, control, autonomous system, and energy system

    WANG Fei-Yue Professor at Institute of Automation, Chinese Academy of Sciences, director of the State Key Laboratory for Management and Control of Complex Systems. Director of China Economic and Social Security Research Center at University of Chinese Academy of Sciences. President of Qingdao Academy of Intelligent Industries. His research interest covers methods and applications for parallel systems, social computing, parallel intelligence, and knowledge automation

  • 摘要:

    随着5G商用规模部署、下一代互联网IPv6的深化应用, 新一代网络技术的发展引发产业界的关注. 网络的智能化被认为是新一代网络发展的趋势. 网络为数字化社会的信息传输提供了基础, 而网络本身的数字化是智能化发展的先决条件. 面向数字化、智能化的新一代网络发展目标, 本文首次系统化提出了 “数字孪生网络(DTN: Digital twin network)” 的概念, 给出了系统架构设计, 分析了DTN的关键技术. 通过对DTN发展挑战的分析, 本文指出了未来 “数字孪生网络” 的发展方向.

  • 图  1  数字孪生网络的核心要素

    Fig.  1  The core elements of digital twin networks

    图  2  数字孪生网络架构

    Fig.  2  Digital twin network architecture

    图  3  基于DTN的意图网络框架

    Fig.  3  Intent network architecture

    图  4  网络遥测系统数据结构

    Fig.  4  Data structure of network telemetry system

    图  5  数据共享仓库功能框架

    Fig.  5  Data sharing warehouse functional framework

    图  6  基于本体的网元和拓扑模型构建流程

    Fig.  6  The process of constructing network element and topology model based on ontology

    表  1  DTN、SDN和平行网络对比

    Table  1  Comparison of DTN, SDN and parallel networks

    维度数字孪生网络 DTN软件定义网络 SDN平行网络
    物理对象各种类型的物理网元具备 SDN 特性的物理网元各种类型的物理网元
    架构层次物理层、孪生层和网络应用层物理层、控制层和管理层物理层、人工网络 + 计算实验层
    虚拟网络物理网络的孪生镜像, 孪生层通过
    统一数据建模构建
    N/A基于人工系统生成物理网络对应的人工网络;
    人工网络基于 SDN 架构构建
    虚实映射通过功能映射模型对网络应用进行仿真和迭代
    优化; 注重虚实映射的实时性和精确性
    N/A通过人工网络逼近物理网络; 更加强调
    计算实验和外在行为的干预
    分析方法基于孪生层的共享数据仓库, 充分利用大数据
    分析、人工智能技术, 通过模型化实例的迭代
    仿真, 实现网络的全局动态实时控制和优化
    只具备基本的网络控制和管
    理能力, 缺乏对于复杂网络
    的动态控制和优化能力
    通过对人工网络(以及人工数据)进行各种实
    验, 对网络行为进行分析和预测, 进而平
    行执行至物理网络并根据反馈迭代优化
    下载: 导出CSV
  • [1] Clemm A, Zhani M F, Boutaba R. Network management 2030: Operations and control of network 2030 services. Journal of Network and Systems Management, 2020, 28(4): 721−750 doi: 10.1007/s10922-020-09517-0
    [2] Taleb T, Aguiar R L, Yahia I G B, Christensen G, Chunduri U, Clemm A, et al. White Paper on 6G Networking. (6G Research Visions, No. 6) [Online], available: http://urn.fi/urn:isbn:9789526226842, June 30, 2020
    [3] Clemm A, Ciavaglia L, Granville L, Tantsura J. Intent-Based Networking - Concepts and Definitions. Internet-Draft: draft-irtf-nmrg-ibn-concepts-definitions-03, February 22, 2021
    [4] CISCO. Intent-based networking [Online], available: https://www.cisco.com/c/en/us/solutions/intent-based-networking.html, March 11, 2021
    [5] JUNIPER. The self-driving network [Online], available: https://www.juniper.net/us/en/insights/the-self-driving-network, March 11, 2021
    [6] HUAWEI. Autonomous driving network [Online], available: https://carrier.huawei.com/en/spotlight/autonomous-driving-network, March 11, 2021
    [7] ETSI. Zero touch network and service management [Online], available: https://www.etsi.org/technologies/zero-touch-network-service-management, March 11, 2021
    [8] Grieves M. Digital twin: Manufacturing excellence through virtual factory replication [Online], available: https://www.3ds.com/fileadmin/PRODUCTS-SERVICES/DELMIA/PDF/Whitepaper/DELMIA-APRISO-Digital-Twin-Whitepaper.pdf, March 11, 2021
    [9] Glaessgen E H, Stargel D S. The digital twin paradigm for future NASA and U.S. air force vehicles. In: Proceedings of the 53rd Structures, Structural Dynamics, and Materials Conference: Special Session on the Digital Twin. Honolulu, Hawaii, USA: AIAA, 2012. 1−14
    [10] Tao F, Zhang H, Liu A, Nee A Y C. Digital twin in industry: State-of-the-art. IEEE Transactions on Industrial Informatics, 2019, 15(4): 2405−2415 doi: 10.1109/TII.2018.2873186
    [11] Tao F, Cheng J F, Qi Q L, Zhang M, Zhang H, Sui F Y. Digital twin-driven product design, manufacturing and service with big data. International Journal of Advanced Manufacturing Technology, 2018, 94(9): 3563−3576
    [12] 刘蔚然, 陶飞, 程江峰, 张连超, 易旺民. 数字孪生卫星: 概念、关键技术及应用. 计算机集成制造系统, 2020, 26(3): 565−588

    Liu Wei-Ran, Tao Fei, Cheng Jiang-Feng, Zhang Lian-Chao, Yi Wang-Min. Digital twin satellite: Concept, key technologies and applications. Computer Integrated Manufacturing Systems, 2020, 26(3): 565−588
    [13] ITU-T. Representative use cases and key network requirements for Network 2030, FG Network 2030 Technical Report, 2020.
    [14] ITU-T. Additional representative use cases and key network requirements for Network 2030. FG Network 2030 Technical Report, 2020.
    [15] Natis Y, Jacobson S, Reynolds M, Velosa A, Lheureux B, Halpern M, et al. Innovation insight for digital twins - driving better IoT-fueled decisions [Online], available: https://www.gartner.com/en/documents/3645341, March 22, 2017
    [16] ISO. Digital Twin framework for manufacturing - Part 1: Overview and general principles: ISO/CD 23247-1 [Online], available: https://www.iso.org/standard/75066.html, March 11, 2021
    [17] ISO. Digital Twin framework for manufacturing - Part 2: Reference architecture: ISO/CD 23247-2 [Online], available: https://www.iso.org/standard/78743.html, March 11, 2021
    [18] 王飞跃. 平行系统方法与复杂系统的管理和控制. 控制与决策, 2004, 19(5): 485−489, 514 doi: 10.3321/j.issn:1001-0920.2004.05.002

    Wang Fei-Yue. Parallel system methods for management and control of complex systems. Control and Decision, 2004, 19(5): 485−489, 514 doi: 10.3321/j.issn:1001-0920.2004.05.002
    [19] 张俊, 许沛东, 王飞跃. 平行系统和数字孪生的一种数据驱动形式表示及计算框架. 自动化学报, 2020, 46(7): 1346−1356

    Zhang Jun, Xu Pei-Dong, Wang Fei-Yue. Parallel systems and digital twins: A data-driven mathematical representation and computational framework. Acta Automatica Sinica, 2020, 46(7): 1346−1356
    [20] 杨林瑶, 陈思远, 王晓, 张俊, 王成红. 数字孪生与平行系统: 发展现状、对比及展望. 自动化学报, 2019, 45(11): 2001−2031

    Yang Lin-Yao, Chen Si-Yuan, Wang Xiao, Zhang Jun, Wang Cheng-Hong. Digital twins and parallel systems: state of the art, comparisons and prospect. Acta Automatica Sinica, 2019, 45(11): 2001−2031
    [21] Negri E, Fumagalli L, Macchi M. A review of the roles of digital twin in CPS-based production systems. Procedia Manufacturing, 2017, 11: 939−948 doi: 10.1016/j.promfg.2017.07.198
    [22] Wang F Y. The emergence of intelligent enterprises: From CPS to CPSS. IEEE Intelligent Systems, 2010, 25(4): 85−88 doi: 10.1109/MIS.2010.104
    [23] 王飞跃, 张梅, 孟祥冰, 王雁, 马娇楠, 刘武, 等. 平行眼: 基于ACP的智能眼科诊疗. 模式识别与人工智能, 2018, 31(6): 495−504

    Wang Fei-Yue, Zhang Mei, Meng Xiang-Bing, Wang Yan, Ma Jiao-Nan, Liu Wu, et al. Parallel eyes: An ACP-based smart ophthalmic diagnosis and treatment. Pattern Recognition and Artificial Intelligence, 2018, 31(6): 495−504
    [24] 王飞跃, 张梅, 孟祥冰, 王蓉, 王晓, 张志成, 等. 平行手术: 基于ACP的智能手术计算方法. 模式识别与人工智能, 2017, 30(11): 961−970

    Wang Fei-Yue, Zhang Mei, Meng Xiang-Bing, Wang Rong, Wang Xiao, Zhang Zhi-Cheng, et al. Parallel surgery: An ACP-based approach for intelligent operations. Pattern Recognition and Artificial Intelligence, 2017, 30(11): 961−970
    [25] Wang F Y, Zheng N N, Cao D P, Martinez C M, Li L, Liu T. Parallel driving in CPSS: A unified approach for transport automation and vehicle intelligence. IEEE/CAA Journal of Automatica Sinica, 2017, 4(4): 577−587 doi: 10.1109/JAS.2017.7510598
    [26] 王飞跃. 面向赛博空间的战争组织与行动: 关于平行军事体系的讨论. 军事运筹与系统工程, 2012, 26(3): 5−10 doi: 10.3969/j.issn.1672-8211.2012.03.002
    [27] Yang L and Wang F. Driving into Intelligent Spaces with Pervasive Communications. IEEE Intelligent Systems, 2007, 22(1): 12−15.
    [28] Hu K. Bridging networks and business intent to activate intelligence [Online], available: https://www.huawei.com/en/about-huawei/publications/communicate/86/bridging-networks-business-intent, Dec. 28, 2018
    [29] ARIA Networks. Tier 1 Operator Goes Live with Automated Traffic Engineering using AI and a ‘Digital Twin’ [Online], available: https://www.aria-networks.com/blog/tier-1-operator-goes-live-with-automated-traffic-engineering-using-ai-and-a-digital-twin/, March 11, 2021
    [30] Yu Q , Ren J , Fu Y J, Li Y. Cybertwin: An origin of next generation network architecture. IEEE Wireless Communications, 2019, 26(6): 111−117.
    [31] Yu Q , Ren J , Zhou H B, Zhang W. A Cybertwin based network architecture for 6G. In: Proceedings of the 2nd 6G Wireless Summit (6G SUMMIT), Levi, Finland: IEEE, Virtual Meeting: IEEE, 2020.
    [32] Dong R, She C Y, Hardjawana W, Li Y H, Vucetic B. Deep learning for hybrid 5G services in mobile edge computing systems: Learn from a digital twin. IEEE Transactions on Wireless Communications, 2019, 18(10): 4692−4707 doi: 10.1109/TWC.2019.2927312
    [33] Dai Y Y, Zhang K, Maharjan S, Zhang Y. Deep reinforcement learning for stochastic computation offloading in digital twin networks. IEEE Transactions on Industrial Informatics, DOI: 10.1109/TII.2020.3016320, to be published
    [34] Sun W, Zhang H B, Wang R, Zhang Y. Reducing offloading latency for digital twin edge networks in 6G. IEEE Transactions on Vehicular Technology, 2020, 69(10): 12240−12251 doi: 10.1109/TVT.2020.3018817
    [35] 王飞跃, 杨坚, 韩双双, 杨柳青, 程翔. 基于平行系统理论的平行网络架构. 指挥与控制学报, 2016, 2(1): 71−77

    Wang Fei-Yue, Yang Jian, Han Shuang-Shuang, Yang Liu-Qing, Cheng Xiang. The framework of parallel network based on the parallel system theory. Journal of Command and Control, 2016, 2(1): 71−77
    [36] 王飞跃, 杨柳青, 胡晓娅, 等. 平行网络与网络软件化: 一种新颖的网络架构. 中国科学: 信息科学, 2017, 47: 811−831 doi: 10.1360/N112016-00047

    Wang Fei-Yue, Yang Liu-Qing, Hu Xiao-Ya, et al. Parallel networks and network softwarization: A novel network architecture. Scientia Sinica Informationis, 2017, 47: 811−831 doi: 10.1360/N112016-00047
    [37] Wang F Y, Yang L Q, Cheng X, Han S S, Yang J. Network softwarization and parallel networks: Beyond software-defined networks. IEEE Network, 2016, 30(4): 60−65 doi: 10.1109/MNET.2016.7513865
    [38] McKeown N, Anderson T, Balakrishnan H, Parulkar G, Peterson L, Rexford J, et al. OpenFlow: Enabling innovation in campus networks. ACM SIGCOMM Computer Communication Review, 2008, 38(2): 69−74 doi: 10.1145/1355734.1355746
    [39] Open Networking Foundation. Software-defined networking: The new norm for networks. ONF White Paper, 2012, 2: 2−6
    [40] Song H, Qin F, Martinez-Julia P, Ciavaglia L, Wang A. Network Telemetry Framework. Internet-Draft: Internet-Draft draft-ietf-opsawg-ntf-07, February 19, 2021
    [41] Quittek J, Zseby T, Claise B, Zander S. Requirements for IP flow information export (IPFIX). IETF RFC 3917, 2004.
    [42] Song H Y, Zhou T R, Li Z B, Shin J, Lee K. Postcard-based on-Path flow data telemetry. Internet-Draft: draft-song-ippm-postcard-based-telemetry-09, February 19, 2021
    [43] Kim C, Sivaraman A, Katta N, Bas A, Dixit A, Wobker L J. In-band network telemetry via programmable dataplanes. In: Proceedings of the 2015 ACM Conference on SIGCOMM. Demo Session, London: ACM, 2015
    [44] Brockners F, Bhandari S, Dara S, Pignataro G, Gredler H, Leddy J, et al. Requirements for in-situ OAM. Internet-Draft: draft-brockners-inband-oam-requirements-03, March 13, 2017
    [45] Lu B, Xu L, Song Y Z, Dai L F, Liu M, Zhou T R, et al. iFIT: Intelligent flow information telemetry. In: Proceedings of the 2019 ACM SIGCOMM Conference Posters and Demos. Beijing, China: ACM, 2019. 15−17
    [46] Inmon W H. 数据仓库. 北京: 机械工业出版社, 2006.

    Inmon W H. Building the Data Warehouse. Beijing: China Machine Press, 2006.
    [47] Studer R, Benjamins V R, Fensel D. Knowledge engineering: Principles and methods. Data & Knowledge Engineering, 1998, 25(1-2): 161−197
    [48] 卜令娟. 基于本体的战场态势一致性关键技术研究[硕士学位论文], 杭州电子科技大学, 中国, 2015.

    Bu Ling-Juan. Research on key technologies in ontology-based battlefield situation consistency [Master thesis], Hangzhou Dianzi University, China, 2015.
    [49] Breiman L. Random forests. Machine Learning, 2001, 45: 5−32 doi: 10.1023/A:1010933404324
    [50] Hu J F, Min J L. Automated detection of driver fatigue based on EEG signals using gradient boosting decision tree model. Cognitive Neurodynamics, 2018, 12(4): 431−440 doi: 10.1007/s11571-018-9485-1
    [51] Chang L, Zhu M L, Gu T L, Bin C Z, Qian J Y, Zhang J. Knowledge graph embedding by dynamic translation. IEEE Access, 2017, 5: 20898−20907 doi: 10.1109/ACCESS.2017.2759139
    [52] Srinivas M, Patnaik L M. Genetic algorithms: A survey. Computer, 1994, 27(6): 17−26 doi: 10.1109/2.294849
    [53] Price K V. Differential evolution. Handbook of Optimization. Berlin: Springer, 2013. 187−214
    [54] Timmis J, Neal M, Hunt J. An artificial immune system for data analysis. Biosystems, 2000, 55(1-3): 143−150 doi: 10.1016/S0303-2647(99)00092-1
    [55] Dorigo M, Maniezzo V, Colorni A. Ant system: Optimization by a colony of cooperating agents. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 1996, 26(1): 29−41 doi: 10.1109/3477.484436
    [56] Kennedy J, Eberhart R. Particle swarm optimization. In: Proceedings of ICNN'95-International Conference on Neural Networks. Perth, WA, Australia: IEEE, 2002. 1942−1948
    [57] Stutton R S, Barto A G. Reinforcement learning. A Bradford Book. Cambridge, MA: MIT Press, 1998.
    [58] Cao X D, Wipf D, Wen F, Duan G Q, Sun J. A practical transfer learning algorithm for face verification. In: Proceedings of the 2013 IEEE International Conference on Computer Vision. Sydney, NSW, Australia: IEEE, 2013. 3208−3215
    [59] Ware C, Purchase H, Colpoys L, McGill M. Cognitive measurements of graph aesthetics. Information Visualization, 2002, 1(2): 103−110 doi: 10.1057/palgrave.ivs.9500013
    [60] 王松, 张野, 吴亚东. 网络拓扑结构可视化方法研究与发展. 网络与信息安全学报, 2018, 4(2): 1−17

    Wang Song, Zhang Ye, Wu Ya-Dong. Survey on network topology visualization. Chinese Journal of Network and Information Security, 2018, 4(2): 1−17
    [61] Wu C Y, Sheng S Y, Dong X J. Research on visualization systems for DDoS attack detection. In: Proceedings of the 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC). Miyazaki, Japan: Miyazaki, 2018. 2986−2991
    [62] Zhang T Y, Wang X M, Li Z Z, Guo F Z, Ma Y X, Chen W. A survey of network anomaly visualization. Science China Information Sciences, 2017, 60(12): 121101 doi: 10.1007/s11432-016-0428-2
    [63] Mansmann F, Keim D A, North S C, Rexroad B, Sheleheda D. Visual analysis of network traffic for resource planning, interactive monitoring, and interpretation of security threats. IEEE Transactions on Visualization and Computer Graphics, 2007, 13(6): 1105−1112 doi: 10.1109/TVCG.2007.70522
    [64] Richardson. L, Amundsen M. RESTful Web APIs. O'Reilly Media, Inc, 2013.
    [65] Woodall T S, Shipman G M, Bosilca G, Graham R L, Maccabe A B. High performance RDMA protocols in HPC. In: Recent Advances in Parallel Virtual Machine and Message Passing Interface. Berlin, Heidelberg: Springer-Verlag, 2006. 76−85
    [66] Iyengar J, Thomson M. QUIC: A UDP-Based Multiplexed and Secure Transport. Internet-Draft: draft-ietf-quic-transport-34, January 14, 2021
    [67] Bishop M. Hypertext Transfer Protocol Version 3 (HTTP/3). Internet-Draft: draft-ietf-quic-http-34, February 2, 2021
  • 加载中
图(6) / 表(1)
计量
  • 文章访问数:  8676
  • HTML全文浏览量:  4948
  • PDF下载量:  2411
  • 被引次数: 0
出版历程
  • 收稿日期:  2021-01-29
  • 录用日期:  2021-03-08
  • 网络出版日期:  2021-04-02
  • 刊出日期:  2021-04-02

目录

    /

    返回文章
    返回