Communication Networks and Service Management in the Era of Artificial Intelligence and Machine Learning. Группа авторов
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56 56 Renga, D., Apiletti, D., Giordano, D. et al. (2020). Data‐driven exploratory models of an electric distribution network for fault prediction and diagnosis. Computing 102 (5): 1199–1211. https://doi.org/10.1007/s00607‐019‐00781‐w.
57 57 Steenwinckel, B., Paepe, D.D., Hautte, S.V. et al. (2021). FLAGS: a methodology for adaptive anomaly detection and root cause analysis on sensor data streams by fusing expert knowledge with machine learning. Future Generation Computer Systems 116: 30–48. https://doi.org/10.1016/j.future.2020.10.015.
58 58 Xie, J., Yu, F.R., Huang, T. et al. (2018). A survey of machine learning techniques applied to software defined networking (SDN): research issues and challenges. IEEE Communication Surveys and Tutorials 21 (1): 393–430.
59 59 Zhang, C., Patras, P., and Haddadi, H. (2019). Deep learning in mobile and wireless networking: a survey. IEEE Communication Surveys and Tutorials. 21 (3)
60 60 Park, S., Kim, H., Hong, J. et al. (2020). Machine learning‐based optimal VNF deployment. 21st Asia‐Pacific Network Operations and Management Symposium, APNOMS 2020, Daegu, South Korea (22–25 September 2020), IEEE, pp. 67–72. https://doi.org/10.23919/APNOMS50412.2020.9236970.
61 61 Lerner, A. (2017). Intent‐based networking. Gartner Blog: https://blogs.gartner.com/andrew-lerner/2017/02/07/intent-based-networking/ (accessed 15 April 2021).
62 62 ETSI (2020). Zero‐touch network and Service Management. https://www.etsi.org/technologies/zero-touch-network-service-management (accessed 13 April 2021).
63 63 Tsvetkov, T., Ali‐Tolppa, J., Sanneck, H., and Carle, G. (2016). Verification of configuration management changes in self‐organizing networks. IEEE Transactions on Network and Service Management 13 (4): 885–898. https://doi.org/10.1109/TNSM.2016.2589459.
64 64 Zhang, Y., Yao, J., and Guan, H. (2017). Intelligent cloud resource management with deep reinforcement learning. IEEE Cloud Computing 4 (6): 60–69. https://doi.org/10.1109/MCC.2018.1081063.
65 65 Mismar, F.B., Choi, J., and Evans, B.L. (2019). A framework for automated cellular network tuning with reinforcement learning. IEEE Transactions on Communications 67 (10): 7152–7167. https://doi.org/10.1109/TCOMM.2019.2926715.
66 66 Yao, H., Mai, T., Jiang, C. et al. (2019). Ai routers network mind: a hybrid machine learning paradigm for packet routing. IEEE Computational Intelligence Magazine 14 (4): 21–30. https://doi.org/10.1109/MCI.2019.2937609.
67 67 Zhang, Q., Wang, X., Lv, J., and Huang, M. (2020). Intelligent content‐aware traffic engineering for SDN: an Ai‐driven approach. IEEE Network 34 (3): 186–193. https://doi.org/10.1109/MNET.001.1900340.
68 68 Zhang, J., Ye, M., Guo, Z. et al. (2020). CFR‐RL: traffic engineering with reinforcement learning in SDN. IEEE Journal on Selected Areas in Communications 38 (10): 2249–2259. https://doi.org/10.1109/JSAC.2020.3000371.
69 69 Le, D.C. and Zincir‐Heywood, N. (2020). A frontier: dependable, reliable and secure machine learning for network/system management. Journal of Network and Systems Management 28 (4): 827–849.
Note
1 1 Subject to other limitations, such as the curse of dimensionality.
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