SCIENCE CHINA Information Sciences, Volume 63 , Issue 6 : 160304(2020) https://doi.org/10.1007/s11432-020-2838-6

Intent defined optical network with artificial intelligence-based automated operation and maintenance

More info
  • ReceivedJan 10, 2020
  • AcceptedMar 16, 2020
  • PublishedMay 9, 2020


Traditionally, the operation and maintenance of optical networks rely on the experience of engineers to configure network parameters, involving command-line interface, middle-ware scripting, and troubleshooting. However, with the emerging of newly B5G applications, the traditional configuration cannot meet the requirement of real-time automatic configuration. Operators need a new configuration way without manual intervention at an underlying optical transport network. To cope with this issue, we propose an intent defined optical network (IDON) architecture toward artificial intelligence-based optical network automated operation and maintenance against service objective, by introducing a self-adapted generation and optimization (SAGO) policy in a customized manner. The IDON platform has three key innovations including intent-orient configuration translation, self-adapted generation and optimization policy, and close-loop intent guarantee operation. Focusing specifically on communication requirements, the IDON uses natural language processing to construct semantic graphs to understand, interact, and create the required network configuration. Then, deep reinforcement learning (DRL) is utilized to find the composition policy that satisfies the requirement of intent through the dynamic integration of fine-grained policies. Finally, the deep neural evolutionary network (DNEN) is introduced to achieve the intent guarantee at the milliseconds level. The feasibility and efficiency are verified on enhanced SDN testbed. Finally, we discuss several related challenges and opportunities for unveiling a promising upcoming future of intent defined optical network.


This work was supported in part by National Natural Science Foundation of China (Grant No. 61871056), Young Elite Scientists Sponsorship Program by CAST (Grant No. 2018QNRC001), Beijing Natural Science Foundation (Grant No. 4202050), Fundamental Research Funds for the Central Universities (Grant Nos. 2018XKJC06, 2019PTB-009), Fund of SKL of IPOC (BUPT) (Grant Nos. IPOC2018A001, IPOC2019ZT01), ZTE Research Fund, and Key Laboratory Fund (Grant Nos. 6142411182112, 614210419042, 61400040503, CEPNT-2017KF-04).


[1] Yang H, Zhao X, Yao Q. Accurate Fault Location using Deep Neural Evolution Network in Cloud Data Center Interconnection. IEEE Trans Cloud Comput, 2020, : 1-1 CrossRef Google Scholar

[2] Musumeci F, Rottondi C, Nag A. An Overview on Application of Machine Learning Techniques in Optical Networks. IEEE Commun Surv Tutorials, 2019, 21: 1383-1408 CrossRef Google Scholar

[3] Casellas R, Martinez R, Vilalta R. Control, Management, and Orchestration of Optical Networks: Evolution, Trends, and Challenges. J Lightwave Technol, 2018, 36: 1390-1402 CrossRef ADS Google Scholar

[4] Tuncer D, Charalambides M, Pavlou G. Management Application Interactions in Software-Based Networks. IEEE Network, 2019, 33: 149-155 CrossRef Google Scholar

[5] López V, Jiménez R, González de Dios . Control Plane Architectures for Elastic Optical Networks [Invited]. J Opt Commun Netw, 2018, 10: A241 CrossRef Google Scholar

[6] Kazemi H, Safari M, Haas H. A Wireless Optical Backhaul Solution for Optical Attocell Networks. IEEE Trans Wireless Commun, 2019, 18: 807-823 CrossRef Google Scholar

[7] Aguado A, Davis M, Peng S. Dynamic Virtual Network Reconfiguration Over SDN Orchestrated Multitechnology Optical Transport Domains. J Lightwave Technol, 2016, 34: 1933-1938 CrossRef ADS Google Scholar

[8] Szyrkowiec T, Santuari M, Chamania M. Automatic Intent-Based Secure Service Creation Through a Multilayer SDN Network Orchestration. J Opt Commun Netw, 2018, 10: 289-297 CrossRef Google Scholar

[9] Choi J S, Chun S J. Performance Analysis of a Hierarchical Inter-Domain Provisioning Framework for Multi-Domain Software-Defined Optical Transport Networks. J Lightwave Technol, 2019, 37: 3834-3843 CrossRef ADS Google Scholar

[10] Yang H, Zhang J, Zhao Y. CSO: cross stratum optimization for optical as a service. IEEE Commun Mag, 2015, 53: 130-139 CrossRef Google Scholar

[11] Yang H, Yuan J, Yao H. Blockchain-Based Hierarchical Trust Networking for JointCloud. IEEE Internet Things J, 2020, 7: 1667-1677 CrossRef Google Scholar

[12] Ayoubi S, Limam N, Salahuddin M A. Machine Learning for Cognitive Network Management. IEEE Commun Mag, 2018, 56: 158-165 CrossRef Google Scholar

[13] Zibar D, Wymeersch H, Lyubomirsky I. Machine learning under the spotlight. Nat Photon, 2017, 11: 749-751 CrossRef ADS Google Scholar

[14] Liu S, Niu B, Li D. DL-Assisted Cross-Layer Orchestration in Software-Defined IP-Over-EONs: From Algorithm Design to System Prototype. J Lightwave Technol, 2019, 37: 4426-4438 CrossRef ADS Google Scholar

[15] Yu A, Zhang J, Yang H. Long-Term Traffic Scheduling Based on Stacked Bidirectional Recurrent Neural Networks in Inter-Datacenter Optical Networks. IEEE Access, 2019, 7: 182296-182308 CrossRef Google Scholar

[16] Zhao X, Yang H, Guo H, et al. Accurate fault location based on deep neural evolution network in optical networks for 5G and beyond. Proc of OFC, 2019: M3J. 5. Google Scholar

[17] Yang H, Zhan K, Kadoch M, et al. BLCS: brain-like based distributed control security in cyber physical systems. IEEE Network,. arXiv Google Scholar

[18] Yao Q, Yang H, Yu A. Transductive Transfer Learning-Based Spectrum Optimization for Resource Reservation in Seven-Core Elastic Optical Networks. J Lightwave Technol, 2019, 37: 4164-4172 CrossRef ADS Google Scholar

[19] Yang H, Zhang J, Ji Y, et al. C-RoFN: multi-stratum resources optimization for cloud-based radio over optical fiber networks. IEEE Commun Mag, 2016, 54: 118--125. Google Scholar

[20] Ji Y, Zhang J, Zhao Y. Prospects and research issues in multi-dimensional all optical networks. Sci China Inf Sci, 2016, 59: 101301 CrossRef Google Scholar

[21] Yang H, Liang Y, Yuan J. Distributed Blockchain-based Trusted Multi-domain Collaboration for Mobile Edge Computing in 5G and beyond. IEEE Trans Ind Inf, 2020, : 1-1 CrossRef Google Scholar

[22] Ji Y, Zhang J, Wang X. Towards converged, collaborative and co-automatic (3C) optical networks. Sci China Inf Sci, 2018, 61: 121301 CrossRef Google Scholar

[23] Yang H, Zhang J, Zhao Y, et al. SUDOI: software defined networking for ubiquitous data center optical interconnection. IEEE Communications Magazine, 2016, 54(2): 86-95 DOI: 10.1109/MCOM.2016.7402266. Google Scholar

[24] Gu R, Zhang S, Ji Y. Network slicing and efficient ONU migration for reliable communications in converged vehicular and fixed access network. Vehicular Commun, 2018, 11: 57-67 CrossRef Google Scholar

[25] Yang H, Liang Y, Yao Q, et al. Blockchain-based Secure Distributed Control for Software Defined Optical Networking. China Commun, 2019, 16: 42--54. Google Scholar

[26] Ferreira P V R, Paffenroth R, Wyglinski A M. Multi-objective Reinforcement Learning for Cognitive Satellite Communications using Deep Neural Network Ensembles. IEEE J Sel Areas Commun, 2018, : 1-1 CrossRef Google Scholar

[27] Yang H, Zhang J, Ji Y. Experimental demonstration of multi-dimensional resources integration for service provisioning in cloud radio over fiber network. Sci Rep, 2016, 6: 30678 CrossRef PubMed ADS Google Scholar

[28] Yang H, Yao Q, Yu A. Resource Assignment Based on Dynamic Fuzzy Clustering in Elastic Optical Networks With Multi-Core Fibers. IEEE Trans Commun, 2019, 67: 3457-3469 CrossRef Google Scholar

[29] Yang H, Wang B, Yao Q. Efficient Hybrid Multi-Faults Location Based on Hopfield Neural Network in 5G Coexisting Radio and Optical Wireless Networks. IEEE Trans Cogn Commun Netw, 2019, 5: 1218-1228 CrossRef Google Scholar

[30] Zhan K, Yang H, Yao Q, et al. Intent Defined Optical Network: Toward Artificial Intelligence-Based Optical Network Automation. OFC2020, San Diego, March 2020: T3J.6. Google Scholar

Copyright 2020  CHINA SCIENCE PUBLISHING & MEDIA LTD.  中国科技出版传媒股份有限公司  版权所有

京ICP备14028887号-23       京公网安备11010102003388号