Abstract

As optical networks undergo rapid development, the trade-offs among higher network service capability, and increasing operating expense (OPEX) about operations, administration and maintenance (OAM) become telecom operators’ key obstacles. Intelligent and automatic OAM is considered to effectively satisfy service requirements, while dampening OPEX growth. In particular, machine learning (ML) has been investigated as a possible method of replacing human image recognition, nature language processing, automatic drive, and so forth. This is because of its essential feature extraction ability. ML application in optical networks was studied in a preliminary way recently. In ML-enabled optical networks, huge data storage and powerful computing resources are required to handle computer-intensive tasks performed in order to analyze features from big data sets. Integration of these two key resources into existing optical network architectures, in order to improve network performance, is an emerging challenge for ML-enabled optical networks. This article proposes a novel optical network architecture, which is based on software-defined networking (SDN), which is also named self-optimizing optical networks (SOON). First, we comb through intelligence development of optical networks, and introduce SOON as an OAM-oriented optical network architecture. Second, we demonstrate four typical applications within SOON, including tidal traffic prediction, alarm prediction, anomaly action detection, and routing and wavelength assignment. Finally, we discuss some open issues.

© 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

Full Article  |  PDF Article
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References

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2017 (4)

D. Silver, J. Schrittwieser, K. Simonyan, I. Antonoglou, A. Huang, A. Guez, T. Hubert, L. Baker, M. Lai, A. Bolton, Y. Chen, T. Lillicrap, F. Hui, L. Sifre, G. van den Driessche, T. Graepel, and D. Hassabis, “Mastering the game of Go without human knowledge,” Nature 550(7676), 354–359 (2017).
[Crossref] [PubMed]

Z. Wang, M. Zhang, D. Wang, C. Song, M. Liu, J. Li, L. Lou, and Z. Liu, “Failure prediction using machine learning and time series in optical network,” Opt. Express 25(16), 18553–18565 (2017).
[Crossref] [PubMed]

H. Zhang, Y. Wang, H. Chen, Y. Zhao, and J. Zhang, “Exploring machine-learning-based control plane intrusion detection techniques in software defined optical networks,” Opt. Fiber Technol. 39, 37–42 (2017).
[Crossref]

R. Li, Z. Zhao, J. Zheng, C. Mei, Y. Cai, and H. Zhang, “The learning and prediction of application-level traffic data in cellular networks,” IEEE Trans. Wirel. Commun. 16(6), 3899–3912 (2017).
[Crossref]

2016 (1)

D. Silver, A. Huang, C. J. Maddison, A. Guez, L. Sifre, G. van den Driessche, J. Schrittwieser, I. Antonoglou, V. Panneershelvam, M. Lanctot, S. Dieleman, D. Grewe, J. Nham, N. Kalchbrenner, I. Sutskever, T. Lillicrap, M. Leach, K. Kavukcuoglu, T. Graepel, and D. Hassabis, “Mastering the game of Go with deep neural networks and tree search,” Nature 529(7587), 484–489 (2016).
[Crossref] [PubMed]

2015 (1)

M. I. Jordan and T. M. Mitchell, “Machine learning: Trends, perspectives, and prospects,” Science 349(6245), 255–260 (2015).
[Crossref] [PubMed]

2014 (2)

2012 (1)

N. Charbonneau and V. Vokkarane, “A survey of advance reservation routing and wavelength assignment in wavelength-routed WDM networks,” IEEE Comm. Surv. and Tutor. 14(4), 1037–1064 (2012).
[Crossref]

2010 (1)

C. Song, Z. Qu, N. Blumm, and A. L. Barabási, “Limits of predictability in human mobility,” Science 327(5968), 1018–1021 (2010).
[Crossref] [PubMed]

2009 (1)

S. Azodolmolky, M. Klinkowski, E. Marin, D. Careglio, J. S. Pareta, and I. Tomkos, “A survey on physical layer impairments aware routing and wavelength assignment algorithms in optical networks,” Comput. Netw. 53(7), 926–944 (2009).
[Crossref]

2003 (1)

A. Ding and G. Poo, “A survey of optical multicast over WDM networks,” Comput. Commun. 26(2), 193–200 (2003).
[Crossref]

Alemi, A. A.

C. Szegedy, S. Ioffe, V. Vanhoucke, and A. A. Alemi, “Inception-v4, inception-ResNet and the impact of residual connections on learning,” Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17), San Francisco, California, USA, Feb. 2017.

Alvizu, R.

S. Troia, G. Sheng, R. Alvizu, G. A. Maier, and A. Pattavina, “Identification of tidal-traffic patterns in metro-area mobile networks via matrix factorization based model,” IEEE International Conference on Pervasive Computing and Communications, Kona, USA, May 2017.
[Crossref]

Antonoglou, I.

D. Silver, J. Schrittwieser, K. Simonyan, I. Antonoglou, A. Huang, A. Guez, T. Hubert, L. Baker, M. Lai, A. Bolton, Y. Chen, T. Lillicrap, F. Hui, L. Sifre, G. van den Driessche, T. Graepel, and D. Hassabis, “Mastering the game of Go without human knowledge,” Nature 550(7676), 354–359 (2017).
[Crossref] [PubMed]

D. Silver, A. Huang, C. J. Maddison, A. Guez, L. Sifre, G. van den Driessche, J. Schrittwieser, I. Antonoglou, V. Panneershelvam, M. Lanctot, S. Dieleman, D. Grewe, J. Nham, N. Kalchbrenner, I. Sutskever, T. Lillicrap, M. Leach, K. Kavukcuoglu, T. Graepel, and D. Hassabis, “Mastering the game of Go with deep neural networks and tree search,” Nature 529(7587), 484–489 (2016).
[Crossref] [PubMed]

Azodolmolky, S.

S. Azodolmolky, M. Klinkowski, E. Marin, D. Careglio, J. S. Pareta, and I. Tomkos, “A survey on physical layer impairments aware routing and wavelength assignment algorithms in optical networks,” Comput. Netw. 53(7), 926–944 (2009).
[Crossref]

Badia, A. P.

V. Mnih, A. P. Badia, M. Mirza, A. Graves, T. Harley, T. P. Lillicrap, D. Silver, and K. Kavukcuoglu, “Asynchronous methods for deep reinforcement learning,” Proceedings of the 33rd International Conference on Machine Learning, New York, NY, USA, 2016.

Baker, L.

D. Silver, J. Schrittwieser, K. Simonyan, I. Antonoglou, A. Huang, A. Guez, T. Hubert, L. Baker, M. Lai, A. Bolton, Y. Chen, T. Lillicrap, F. Hui, L. Sifre, G. van den Driessche, T. Graepel, and D. Hassabis, “Mastering the game of Go without human knowledge,” Nature 550(7676), 354–359 (2017).
[Crossref] [PubMed]

Barabási, A. L.

C. Song, Z. Qu, N. Blumm, and A. L. Barabási, “Limits of predictability in human mobility,” Science 327(5968), 1018–1021 (2010).
[Crossref] [PubMed]

Blumm, N.

C. Song, Z. Qu, N. Blumm, and A. L. Barabási, “Limits of predictability in human mobility,” Science 327(5968), 1018–1021 (2010).
[Crossref] [PubMed]

Bolton, A.

D. Silver, J. Schrittwieser, K. Simonyan, I. Antonoglou, A. Huang, A. Guez, T. Hubert, L. Baker, M. Lai, A. Bolton, Y. Chen, T. Lillicrap, F. Hui, L. Sifre, G. van den Driessche, T. Graepel, and D. Hassabis, “Mastering the game of Go without human knowledge,” Nature 550(7676), 354–359 (2017).
[Crossref] [PubMed]

Bresson, X.

M. Brinstein, J. Bruna, X. Bresson, and Y. LeCun, “Geometric deep learning on graphs and manifolds,” Proceedings of Conference on Neural Information Processing Systems, Los Angeles, California, USA, Sept. 2017.

Brinstein, M.

M. Brinstein, J. Bruna, X. Bresson, and Y. LeCun, “Geometric deep learning on graphs and manifolds,” Proceedings of Conference on Neural Information Processing Systems, Los Angeles, California, USA, Sept. 2017.

Bruna, J.

M. Brinstein, J. Bruna, X. Bresson, and Y. LeCun, “Geometric deep learning on graphs and manifolds,” Proceedings of Conference on Neural Information Processing Systems, Los Angeles, California, USA, Sept. 2017.

Cai, Y.

R. Li, Z. Zhao, J. Zheng, C. Mei, Y. Cai, and H. Zhang, “The learning and prediction of application-level traffic data in cellular networks,” IEEE Trans. Wirel. Commun. 16(6), 3899–3912 (2017).
[Crossref]

Careglio, D.

S. Azodolmolky, M. Klinkowski, E. Marin, D. Careglio, J. S. Pareta, and I. Tomkos, “A survey on physical layer impairments aware routing and wavelength assignment algorithms in optical networks,” Comput. Netw. 53(7), 926–944 (2009).
[Crossref]

Charbonneau, N.

N. Charbonneau and V. Vokkarane, “A survey of advance reservation routing and wavelength assignment in wavelength-routed WDM networks,” IEEE Comm. Surv. and Tutor. 14(4), 1037–1064 (2012).
[Crossref]

Chen, H.

H. Zhang, Y. Wang, H. Chen, Y. Zhao, and J. Zhang, “Exploring machine-learning-based control plane intrusion detection techniques in software defined optical networks,” Opt. Fiber Technol. 39, 37–42 (2017).
[Crossref]

Y. Zhao, R. He, H. Chen, J. Zhang, Y. Ji, H. Zheng, Y. Lin, and X. Wang, “Experimental performance evaluation of software defined networking (SDN) based data communication networks for large scale flexi-grid optical networks,” Opt. Express 22(8), 9538–9547 (2014).
[Crossref] [PubMed]

Chen, Y.

D. Silver, J. Schrittwieser, K. Simonyan, I. Antonoglou, A. Huang, A. Guez, T. Hubert, L. Baker, M. Lai, A. Bolton, Y. Chen, T. Lillicrap, F. Hui, L. Sifre, G. van den Driessche, T. Graepel, and D. Hassabis, “Mastering the game of Go without human knowledge,” Nature 550(7676), 354–359 (2017).
[Crossref] [PubMed]

Dieleman, S.

D. Silver, A. Huang, C. J. Maddison, A. Guez, L. Sifre, G. van den Driessche, J. Schrittwieser, I. Antonoglou, V. Panneershelvam, M. Lanctot, S. Dieleman, D. Grewe, J. Nham, N. Kalchbrenner, I. Sutskever, T. Lillicrap, M. Leach, K. Kavukcuoglu, T. Graepel, and D. Hassabis, “Mastering the game of Go with deep neural networks and tree search,” Nature 529(7587), 484–489 (2016).
[Crossref] [PubMed]

Ding, A.

A. Ding and G. Poo, “A survey of optical multicast over WDM networks,” Comput. Commun. 26(2), 193–200 (2003).
[Crossref]

Graepel, T.

D. Silver, J. Schrittwieser, K. Simonyan, I. Antonoglou, A. Huang, A. Guez, T. Hubert, L. Baker, M. Lai, A. Bolton, Y. Chen, T. Lillicrap, F. Hui, L. Sifre, G. van den Driessche, T. Graepel, and D. Hassabis, “Mastering the game of Go without human knowledge,” Nature 550(7676), 354–359 (2017).
[Crossref] [PubMed]

D. Silver, A. Huang, C. J. Maddison, A. Guez, L. Sifre, G. van den Driessche, J. Schrittwieser, I. Antonoglou, V. Panneershelvam, M. Lanctot, S. Dieleman, D. Grewe, J. Nham, N. Kalchbrenner, I. Sutskever, T. Lillicrap, M. Leach, K. Kavukcuoglu, T. Graepel, and D. Hassabis, “Mastering the game of Go with deep neural networks and tree search,” Nature 529(7587), 484–489 (2016).
[Crossref] [PubMed]

Graves, A.

V. Mnih, A. P. Badia, M. Mirza, A. Graves, T. Harley, T. P. Lillicrap, D. Silver, and K. Kavukcuoglu, “Asynchronous methods for deep reinforcement learning,” Proceedings of the 33rd International Conference on Machine Learning, New York, NY, USA, 2016.

Grewe, D.

D. Silver, A. Huang, C. J. Maddison, A. Guez, L. Sifre, G. van den Driessche, J. Schrittwieser, I. Antonoglou, V. Panneershelvam, M. Lanctot, S. Dieleman, D. Grewe, J. Nham, N. Kalchbrenner, I. Sutskever, T. Lillicrap, M. Leach, K. Kavukcuoglu, T. Graepel, and D. Hassabis, “Mastering the game of Go with deep neural networks and tree search,” Nature 529(7587), 484–489 (2016).
[Crossref] [PubMed]

Guez, A.

D. Silver, J. Schrittwieser, K. Simonyan, I. Antonoglou, A. Huang, A. Guez, T. Hubert, L. Baker, M. Lai, A. Bolton, Y. Chen, T. Lillicrap, F. Hui, L. Sifre, G. van den Driessche, T. Graepel, and D. Hassabis, “Mastering the game of Go without human knowledge,” Nature 550(7676), 354–359 (2017).
[Crossref] [PubMed]

D. Silver, A. Huang, C. J. Maddison, A. Guez, L. Sifre, G. van den Driessche, J. Schrittwieser, I. Antonoglou, V. Panneershelvam, M. Lanctot, S. Dieleman, D. Grewe, J. Nham, N. Kalchbrenner, I. Sutskever, T. Lillicrap, M. Leach, K. Kavukcuoglu, T. Graepel, and D. Hassabis, “Mastering the game of Go with deep neural networks and tree search,” Nature 529(7587), 484–489 (2016).
[Crossref] [PubMed]

Harley, T.

V. Mnih, A. P. Badia, M. Mirza, A. Graves, T. Harley, T. P. Lillicrap, D. Silver, and K. Kavukcuoglu, “Asynchronous methods for deep reinforcement learning,” Proceedings of the 33rd International Conference on Machine Learning, New York, NY, USA, 2016.

Hassabis, D.

D. Silver, J. Schrittwieser, K. Simonyan, I. Antonoglou, A. Huang, A. Guez, T. Hubert, L. Baker, M. Lai, A. Bolton, Y. Chen, T. Lillicrap, F. Hui, L. Sifre, G. van den Driessche, T. Graepel, and D. Hassabis, “Mastering the game of Go without human knowledge,” Nature 550(7676), 354–359 (2017).
[Crossref] [PubMed]

D. Silver, A. Huang, C. J. Maddison, A. Guez, L. Sifre, G. van den Driessche, J. Schrittwieser, I. Antonoglou, V. Panneershelvam, M. Lanctot, S. Dieleman, D. Grewe, J. Nham, N. Kalchbrenner, I. Sutskever, T. Lillicrap, M. Leach, K. Kavukcuoglu, T. Graepel, and D. Hassabis, “Mastering the game of Go with deep neural networks and tree search,” Nature 529(7587), 484–489 (2016).
[Crossref] [PubMed]

He, K.

K. He, X. Zhang, S. Ren, and J. Sun, “Deep residual learning for image recognition,” Proceedings of the IEEE conference on computer vision and pattern recognition, Boston, Massachusetts, USA, June 2015.

He, R.

Hinton, G. E.

A. Krizhevsky, I. Sutskever, and G. E. Hinton, “ImageNet classification with deep convolutional neural networks,” NIPS Conference Proceedings, Lake Tahoe, Nevada, USA, December 2012.

V. Nair and G. E. Hinton, “Rectified linear units improve restricted boltzmann machines,” Proceedings of the 27th international conference on machine learning (ICML-10), Haifa, Israel, June 2010.

Hua, N.

Z. Zhong, N. Hua, H. Li, Y. Li, and X. Zheng, “Considerations of effective tidal traffic dispatching in software-defined metro IP over optical networks,” Opto-Electronics and Communications Conference (OECC), Shanghai, China, June 2015.
[Crossref]

Huang, A.

D. Silver, J. Schrittwieser, K. Simonyan, I. Antonoglou, A. Huang, A. Guez, T. Hubert, L. Baker, M. Lai, A. Bolton, Y. Chen, T. Lillicrap, F. Hui, L. Sifre, G. van den Driessche, T. Graepel, and D. Hassabis, “Mastering the game of Go without human knowledge,” Nature 550(7676), 354–359 (2017).
[Crossref] [PubMed]

D. Silver, A. Huang, C. J. Maddison, A. Guez, L. Sifre, G. van den Driessche, J. Schrittwieser, I. Antonoglou, V. Panneershelvam, M. Lanctot, S. Dieleman, D. Grewe, J. Nham, N. Kalchbrenner, I. Sutskever, T. Lillicrap, M. Leach, K. Kavukcuoglu, T. Graepel, and D. Hassabis, “Mastering the game of Go with deep neural networks and tree search,” Nature 529(7587), 484–489 (2016).
[Crossref] [PubMed]

Hubert, T.

D. Silver, J. Schrittwieser, K. Simonyan, I. Antonoglou, A. Huang, A. Guez, T. Hubert, L. Baker, M. Lai, A. Bolton, Y. Chen, T. Lillicrap, F. Hui, L. Sifre, G. van den Driessche, T. Graepel, and D. Hassabis, “Mastering the game of Go without human knowledge,” Nature 550(7676), 354–359 (2017).
[Crossref] [PubMed]

Hui, F.

D. Silver, J. Schrittwieser, K. Simonyan, I. Antonoglou, A. Huang, A. Guez, T. Hubert, L. Baker, M. Lai, A. Bolton, Y. Chen, T. Lillicrap, F. Hui, L. Sifre, G. van den Driessche, T. Graepel, and D. Hassabis, “Mastering the game of Go without human knowledge,” Nature 550(7676), 354–359 (2017).
[Crossref] [PubMed]

Ioffe, S.

C. Szegedy, S. Ioffe, V. Vanhoucke, and A. A. Alemi, “Inception-v4, inception-ResNet and the impact of residual connections on learning,” Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17), San Francisco, California, USA, Feb. 2017.

S. Ioffe and C. Szegedy, “Batch normalization: accelerating deep network training by reducing internal covariate shift,” Proceedings of the 32 nd International Conference on Machine Learning, Lille, France, 2015.

Ji, Y.

Jordan, M. I.

M. I. Jordan and T. M. Mitchell, “Machine learning: Trends, perspectives, and prospects,” Science 349(6245), 255–260 (2015).
[Crossref] [PubMed]

Kalchbrenner, N.

D. Silver, A. Huang, C. J. Maddison, A. Guez, L. Sifre, G. van den Driessche, J. Schrittwieser, I. Antonoglou, V. Panneershelvam, M. Lanctot, S. Dieleman, D. Grewe, J. Nham, N. Kalchbrenner, I. Sutskever, T. Lillicrap, M. Leach, K. Kavukcuoglu, T. Graepel, and D. Hassabis, “Mastering the game of Go with deep neural networks and tree search,” Nature 529(7587), 484–489 (2016).
[Crossref] [PubMed]

Kavukcuoglu, K.

D. Silver, A. Huang, C. J. Maddison, A. Guez, L. Sifre, G. van den Driessche, J. Schrittwieser, I. Antonoglou, V. Panneershelvam, M. Lanctot, S. Dieleman, D. Grewe, J. Nham, N. Kalchbrenner, I. Sutskever, T. Lillicrap, M. Leach, K. Kavukcuoglu, T. Graepel, and D. Hassabis, “Mastering the game of Go with deep neural networks and tree search,” Nature 529(7587), 484–489 (2016).
[Crossref] [PubMed]

V. Mnih, A. P. Badia, M. Mirza, A. Graves, T. Harley, T. P. Lillicrap, D. Silver, and K. Kavukcuoglu, “Asynchronous methods for deep reinforcement learning,” Proceedings of the 33rd International Conference on Machine Learning, New York, NY, USA, 2016.

Klinkowski, M.

S. Azodolmolky, M. Klinkowski, E. Marin, D. Careglio, J. S. Pareta, and I. Tomkos, “A survey on physical layer impairments aware routing and wavelength assignment algorithms in optical networks,” Comput. Netw. 53(7), 926–944 (2009).
[Crossref]

Krizhevsky, A.

A. Krizhevsky, I. Sutskever, and G. E. Hinton, “ImageNet classification with deep convolutional neural networks,” NIPS Conference Proceedings, Lake Tahoe, Nevada, USA, December 2012.

Lai, M.

D. Silver, J. Schrittwieser, K. Simonyan, I. Antonoglou, A. Huang, A. Guez, T. Hubert, L. Baker, M. Lai, A. Bolton, Y. Chen, T. Lillicrap, F. Hui, L. Sifre, G. van den Driessche, T. Graepel, and D. Hassabis, “Mastering the game of Go without human knowledge,” Nature 550(7676), 354–359 (2017).
[Crossref] [PubMed]

Lanctot, M.

D. Silver, A. Huang, C. J. Maddison, A. Guez, L. Sifre, G. van den Driessche, J. Schrittwieser, I. Antonoglou, V. Panneershelvam, M. Lanctot, S. Dieleman, D. Grewe, J. Nham, N. Kalchbrenner, I. Sutskever, T. Lillicrap, M. Leach, K. Kavukcuoglu, T. Graepel, and D. Hassabis, “Mastering the game of Go with deep neural networks and tree search,” Nature 529(7587), 484–489 (2016).
[Crossref] [PubMed]

Leach, M.

D. Silver, A. Huang, C. J. Maddison, A. Guez, L. Sifre, G. van den Driessche, J. Schrittwieser, I. Antonoglou, V. Panneershelvam, M. Lanctot, S. Dieleman, D. Grewe, J. Nham, N. Kalchbrenner, I. Sutskever, T. Lillicrap, M. Leach, K. Kavukcuoglu, T. Graepel, and D. Hassabis, “Mastering the game of Go with deep neural networks and tree search,” Nature 529(7587), 484–489 (2016).
[Crossref] [PubMed]

LeCun, Y.

M. Brinstein, J. Bruna, X. Bresson, and Y. LeCun, “Geometric deep learning on graphs and manifolds,” Proceedings of Conference on Neural Information Processing Systems, Los Angeles, California, USA, Sept. 2017.

Li, H.

Z. Zhong, N. Hua, H. Li, Y. Li, and X. Zheng, “Considerations of effective tidal traffic dispatching in software-defined metro IP over optical networks,” Opto-Electronics and Communications Conference (OECC), Shanghai, China, June 2015.
[Crossref]

Li, J.

Li, R.

R. Li, Z. Zhao, J. Zheng, C. Mei, Y. Cai, and H. Zhang, “The learning and prediction of application-level traffic data in cellular networks,” IEEE Trans. Wirel. Commun. 16(6), 3899–3912 (2017).
[Crossref]

Li, Y.

Z. Zhong, N. Hua, H. Li, Y. Li, and X. Zheng, “Considerations of effective tidal traffic dispatching in software-defined metro IP over optical networks,” Opto-Electronics and Communications Conference (OECC), Shanghai, China, June 2015.
[Crossref]

Lillicrap, T.

D. Silver, J. Schrittwieser, K. Simonyan, I. Antonoglou, A. Huang, A. Guez, T. Hubert, L. Baker, M. Lai, A. Bolton, Y. Chen, T. Lillicrap, F. Hui, L. Sifre, G. van den Driessche, T. Graepel, and D. Hassabis, “Mastering the game of Go without human knowledge,” Nature 550(7676), 354–359 (2017).
[Crossref] [PubMed]

D. Silver, A. Huang, C. J. Maddison, A. Guez, L. Sifre, G. van den Driessche, J. Schrittwieser, I. Antonoglou, V. Panneershelvam, M. Lanctot, S. Dieleman, D. Grewe, J. Nham, N. Kalchbrenner, I. Sutskever, T. Lillicrap, M. Leach, K. Kavukcuoglu, T. Graepel, and D. Hassabis, “Mastering the game of Go with deep neural networks and tree search,” Nature 529(7587), 484–489 (2016).
[Crossref] [PubMed]

Lillicrap, T. P.

V. Mnih, A. P. Badia, M. Mirza, A. Graves, T. Harley, T. P. Lillicrap, D. Silver, and K. Kavukcuoglu, “Asynchronous methods for deep reinforcement learning,” Proceedings of the 33rd International Conference on Machine Learning, New York, NY, USA, 2016.

Lin, Y.

Liu, M.

Liu, Z.

Lou, L.

Maddison, C. J.

D. Silver, A. Huang, C. J. Maddison, A. Guez, L. Sifre, G. van den Driessche, J. Schrittwieser, I. Antonoglou, V. Panneershelvam, M. Lanctot, S. Dieleman, D. Grewe, J. Nham, N. Kalchbrenner, I. Sutskever, T. Lillicrap, M. Leach, K. Kavukcuoglu, T. Graepel, and D. Hassabis, “Mastering the game of Go with deep neural networks and tree search,” Nature 529(7587), 484–489 (2016).
[Crossref] [PubMed]

Maier, G. A.

S. Troia, G. Sheng, R. Alvizu, G. A. Maier, and A. Pattavina, “Identification of tidal-traffic patterns in metro-area mobile networks via matrix factorization based model,” IEEE International Conference on Pervasive Computing and Communications, Kona, USA, May 2017.
[Crossref]

Marin, E.

S. Azodolmolky, M. Klinkowski, E. Marin, D. Careglio, J. S. Pareta, and I. Tomkos, “A survey on physical layer impairments aware routing and wavelength assignment algorithms in optical networks,” Comput. Netw. 53(7), 926–944 (2009).
[Crossref]

Mei, C.

R. Li, Z. Zhao, J. Zheng, C. Mei, Y. Cai, and H. Zhang, “The learning and prediction of application-level traffic data in cellular networks,” IEEE Trans. Wirel. Commun. 16(6), 3899–3912 (2017).
[Crossref]

Mirza, M.

V. Mnih, A. P. Badia, M. Mirza, A. Graves, T. Harley, T. P. Lillicrap, D. Silver, and K. Kavukcuoglu, “Asynchronous methods for deep reinforcement learning,” Proceedings of the 33rd International Conference on Machine Learning, New York, NY, USA, 2016.

Mitchell, T. M.

M. I. Jordan and T. M. Mitchell, “Machine learning: Trends, perspectives, and prospects,” Science 349(6245), 255–260 (2015).
[Crossref] [PubMed]

Mnih, V.

V. Mnih, A. P. Badia, M. Mirza, A. Graves, T. Harley, T. P. Lillicrap, D. Silver, and K. Kavukcuoglu, “Asynchronous methods for deep reinforcement learning,” Proceedings of the 33rd International Conference on Machine Learning, New York, NY, USA, 2016.

Nair, V.

V. Nair and G. E. Hinton, “Rectified linear units improve restricted boltzmann machines,” Proceedings of the 27th international conference on machine learning (ICML-10), Haifa, Israel, June 2010.

Nham, J.

D. Silver, A. Huang, C. J. Maddison, A. Guez, L. Sifre, G. van den Driessche, J. Schrittwieser, I. Antonoglou, V. Panneershelvam, M. Lanctot, S. Dieleman, D. Grewe, J. Nham, N. Kalchbrenner, I. Sutskever, T. Lillicrap, M. Leach, K. Kavukcuoglu, T. Graepel, and D. Hassabis, “Mastering the game of Go with deep neural networks and tree search,” Nature 529(7587), 484–489 (2016).
[Crossref] [PubMed]

Panneershelvam, V.

D. Silver, A. Huang, C. J. Maddison, A. Guez, L. Sifre, G. van den Driessche, J. Schrittwieser, I. Antonoglou, V. Panneershelvam, M. Lanctot, S. Dieleman, D. Grewe, J. Nham, N. Kalchbrenner, I. Sutskever, T. Lillicrap, M. Leach, K. Kavukcuoglu, T. Graepel, and D. Hassabis, “Mastering the game of Go with deep neural networks and tree search,” Nature 529(7587), 484–489 (2016).
[Crossref] [PubMed]

Pareta, J. S.

S. Azodolmolky, M. Klinkowski, E. Marin, D. Careglio, J. S. Pareta, and I. Tomkos, “A survey on physical layer impairments aware routing and wavelength assignment algorithms in optical networks,” Comput. Netw. 53(7), 926–944 (2009).
[Crossref]

Pattavina, A.

S. Troia, G. Sheng, R. Alvizu, G. A. Maier, and A. Pattavina, “Identification of tidal-traffic patterns in metro-area mobile networks via matrix factorization based model,” IEEE International Conference on Pervasive Computing and Communications, Kona, USA, May 2017.
[Crossref]

Poo, G.

A. Ding and G. Poo, “A survey of optical multicast over WDM networks,” Comput. Commun. 26(2), 193–200 (2003).
[Crossref]

Qu, Z.

C. Song, Z. Qu, N. Blumm, and A. L. Barabási, “Limits of predictability in human mobility,” Science 327(5968), 1018–1021 (2010).
[Crossref] [PubMed]

Ren, S.

K. He, X. Zhang, S. Ren, and J. Sun, “Deep residual learning for image recognition,” Proceedings of the IEEE conference on computer vision and pattern recognition, Boston, Massachusetts, USA, June 2015.

Schrittwieser, J.

D. Silver, J. Schrittwieser, K. Simonyan, I. Antonoglou, A. Huang, A. Guez, T. Hubert, L. Baker, M. Lai, A. Bolton, Y. Chen, T. Lillicrap, F. Hui, L. Sifre, G. van den Driessche, T. Graepel, and D. Hassabis, “Mastering the game of Go without human knowledge,” Nature 550(7676), 354–359 (2017).
[Crossref] [PubMed]

D. Silver, A. Huang, C. J. Maddison, A. Guez, L. Sifre, G. van den Driessche, J. Schrittwieser, I. Antonoglou, V. Panneershelvam, M. Lanctot, S. Dieleman, D. Grewe, J. Nham, N. Kalchbrenner, I. Sutskever, T. Lillicrap, M. Leach, K. Kavukcuoglu, T. Graepel, and D. Hassabis, “Mastering the game of Go with deep neural networks and tree search,” Nature 529(7587), 484–489 (2016).
[Crossref] [PubMed]

Sheng, G.

S. Troia, G. Sheng, R. Alvizu, G. A. Maier, and A. Pattavina, “Identification of tidal-traffic patterns in metro-area mobile networks via matrix factorization based model,” IEEE International Conference on Pervasive Computing and Communications, Kona, USA, May 2017.
[Crossref]

Sifre, L.

D. Silver, J. Schrittwieser, K. Simonyan, I. Antonoglou, A. Huang, A. Guez, T. Hubert, L. Baker, M. Lai, A. Bolton, Y. Chen, T. Lillicrap, F. Hui, L. Sifre, G. van den Driessche, T. Graepel, and D. Hassabis, “Mastering the game of Go without human knowledge,” Nature 550(7676), 354–359 (2017).
[Crossref] [PubMed]

D. Silver, A. Huang, C. J. Maddison, A. Guez, L. Sifre, G. van den Driessche, J. Schrittwieser, I. Antonoglou, V. Panneershelvam, M. Lanctot, S. Dieleman, D. Grewe, J. Nham, N. Kalchbrenner, I. Sutskever, T. Lillicrap, M. Leach, K. Kavukcuoglu, T. Graepel, and D. Hassabis, “Mastering the game of Go with deep neural networks and tree search,” Nature 529(7587), 484–489 (2016).
[Crossref] [PubMed]

Silver, D.

D. Silver, J. Schrittwieser, K. Simonyan, I. Antonoglou, A. Huang, A. Guez, T. Hubert, L. Baker, M. Lai, A. Bolton, Y. Chen, T. Lillicrap, F. Hui, L. Sifre, G. van den Driessche, T. Graepel, and D. Hassabis, “Mastering the game of Go without human knowledge,” Nature 550(7676), 354–359 (2017).
[Crossref] [PubMed]

D. Silver, A. Huang, C. J. Maddison, A. Guez, L. Sifre, G. van den Driessche, J. Schrittwieser, I. Antonoglou, V. Panneershelvam, M. Lanctot, S. Dieleman, D. Grewe, J. Nham, N. Kalchbrenner, I. Sutskever, T. Lillicrap, M. Leach, K. Kavukcuoglu, T. Graepel, and D. Hassabis, “Mastering the game of Go with deep neural networks and tree search,” Nature 529(7587), 484–489 (2016).
[Crossref] [PubMed]

V. Mnih, A. P. Badia, M. Mirza, A. Graves, T. Harley, T. P. Lillicrap, D. Silver, and K. Kavukcuoglu, “Asynchronous methods for deep reinforcement learning,” Proceedings of the 33rd International Conference on Machine Learning, New York, NY, USA, 2016.

Simonyan, K.

D. Silver, J. Schrittwieser, K. Simonyan, I. Antonoglou, A. Huang, A. Guez, T. Hubert, L. Baker, M. Lai, A. Bolton, Y. Chen, T. Lillicrap, F. Hui, L. Sifre, G. van den Driessche, T. Graepel, and D. Hassabis, “Mastering the game of Go without human knowledge,” Nature 550(7676), 354–359 (2017).
[Crossref] [PubMed]

Song, C.

Sun, J.

K. He, X. Zhang, S. Ren, and J. Sun, “Deep residual learning for image recognition,” Proceedings of the IEEE conference on computer vision and pattern recognition, Boston, Massachusetts, USA, June 2015.

Sutskever, I.

D. Silver, A. Huang, C. J. Maddison, A. Guez, L. Sifre, G. van den Driessche, J. Schrittwieser, I. Antonoglou, V. Panneershelvam, M. Lanctot, S. Dieleman, D. Grewe, J. Nham, N. Kalchbrenner, I. Sutskever, T. Lillicrap, M. Leach, K. Kavukcuoglu, T. Graepel, and D. Hassabis, “Mastering the game of Go with deep neural networks and tree search,” Nature 529(7587), 484–489 (2016).
[Crossref] [PubMed]

A. Krizhevsky, I. Sutskever, and G. E. Hinton, “ImageNet classification with deep convolutional neural networks,” NIPS Conference Proceedings, Lake Tahoe, Nevada, USA, December 2012.

Szegedy, C.

S. Ioffe and C. Szegedy, “Batch normalization: accelerating deep network training by reducing internal covariate shift,” Proceedings of the 32 nd International Conference on Machine Learning, Lille, France, 2015.

C. Szegedy, S. Ioffe, V. Vanhoucke, and A. A. Alemi, “Inception-v4, inception-ResNet and the impact of residual connections on learning,” Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17), San Francisco, California, USA, Feb. 2017.

Tomkos, I.

S. Azodolmolky, M. Klinkowski, E. Marin, D. Careglio, J. S. Pareta, and I. Tomkos, “A survey on physical layer impairments aware routing and wavelength assignment algorithms in optical networks,” Comput. Netw. 53(7), 926–944 (2009).
[Crossref]

Troia, S.

S. Troia, G. Sheng, R. Alvizu, G. A. Maier, and A. Pattavina, “Identification of tidal-traffic patterns in metro-area mobile networks via matrix factorization based model,” IEEE International Conference on Pervasive Computing and Communications, Kona, USA, May 2017.
[Crossref]

van den Driessche, G.

D. Silver, J. Schrittwieser, K. Simonyan, I. Antonoglou, A. Huang, A. Guez, T. Hubert, L. Baker, M. Lai, A. Bolton, Y. Chen, T. Lillicrap, F. Hui, L. Sifre, G. van den Driessche, T. Graepel, and D. Hassabis, “Mastering the game of Go without human knowledge,” Nature 550(7676), 354–359 (2017).
[Crossref] [PubMed]

D. Silver, A. Huang, C. J. Maddison, A. Guez, L. Sifre, G. van den Driessche, J. Schrittwieser, I. Antonoglou, V. Panneershelvam, M. Lanctot, S. Dieleman, D. Grewe, J. Nham, N. Kalchbrenner, I. Sutskever, T. Lillicrap, M. Leach, K. Kavukcuoglu, T. Graepel, and D. Hassabis, “Mastering the game of Go with deep neural networks and tree search,” Nature 529(7587), 484–489 (2016).
[Crossref] [PubMed]

Vanhoucke, V.

C. Szegedy, S. Ioffe, V. Vanhoucke, and A. A. Alemi, “Inception-v4, inception-ResNet and the impact of residual connections on learning,” Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17), San Francisco, California, USA, Feb. 2017.

Vokkarane, V.

N. Charbonneau and V. Vokkarane, “A survey of advance reservation routing and wavelength assignment in wavelength-routed WDM networks,” IEEE Comm. Surv. and Tutor. 14(4), 1037–1064 (2012).
[Crossref]

Wang, D.

Wang, X.

Wang, Y.

H. Zhang, Y. Wang, H. Chen, Y. Zhao, and J. Zhang, “Exploring machine-learning-based control plane intrusion detection techniques in software defined optical networks,” Opt. Fiber Technol. 39, 37–42 (2017).
[Crossref]

Wang, Z.

Zhang, H.

H. Zhang, Y. Wang, H. Chen, Y. Zhao, and J. Zhang, “Exploring machine-learning-based control plane intrusion detection techniques in software defined optical networks,” Opt. Fiber Technol. 39, 37–42 (2017).
[Crossref]

R. Li, Z. Zhao, J. Zheng, C. Mei, Y. Cai, and H. Zhang, “The learning and prediction of application-level traffic data in cellular networks,” IEEE Trans. Wirel. Commun. 16(6), 3899–3912 (2017).
[Crossref]

Zhang, J.

H. Zhang, Y. Wang, H. Chen, Y. Zhao, and J. Zhang, “Exploring machine-learning-based control plane intrusion detection techniques in software defined optical networks,” Opt. Fiber Technol. 39, 37–42 (2017).
[Crossref]

Y. Zhao, R. He, H. Chen, J. Zhang, Y. Ji, H. Zheng, Y. Lin, and X. Wang, “Experimental performance evaluation of software defined networking (SDN) based data communication networks for large scale flexi-grid optical networks,” Opt. Express 22(8), 9538–9547 (2014).
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Y. Ji, J. Zhang, and Y. Zhao, “Development prospects of software defined optical networks,” Telecommunications Science 30(8), 19–22 (2014).

Zhang, M.

Zhang, X.

K. He, X. Zhang, S. Ren, and J. Sun, “Deep residual learning for image recognition,” Proceedings of the IEEE conference on computer vision and pattern recognition, Boston, Massachusetts, USA, June 2015.

Zhao, Y.

H. Zhang, Y. Wang, H. Chen, Y. Zhao, and J. Zhang, “Exploring machine-learning-based control plane intrusion detection techniques in software defined optical networks,” Opt. Fiber Technol. 39, 37–42 (2017).
[Crossref]

Y. Zhao, R. He, H. Chen, J. Zhang, Y. Ji, H. Zheng, Y. Lin, and X. Wang, “Experimental performance evaluation of software defined networking (SDN) based data communication networks for large scale flexi-grid optical networks,” Opt. Express 22(8), 9538–9547 (2014).
[Crossref] [PubMed]

Y. Ji, J. Zhang, and Y. Zhao, “Development prospects of software defined optical networks,” Telecommunications Science 30(8), 19–22 (2014).

Zhao, Z.

R. Li, Z. Zhao, J. Zheng, C. Mei, Y. Cai, and H. Zhang, “The learning and prediction of application-level traffic data in cellular networks,” IEEE Trans. Wirel. Commun. 16(6), 3899–3912 (2017).
[Crossref]

Zheng, H.

Zheng, J.

R. Li, Z. Zhao, J. Zheng, C. Mei, Y. Cai, and H. Zhang, “The learning and prediction of application-level traffic data in cellular networks,” IEEE Trans. Wirel. Commun. 16(6), 3899–3912 (2017).
[Crossref]

Zheng, X.

Z. Zhong, N. Hua, H. Li, Y. Li, and X. Zheng, “Considerations of effective tidal traffic dispatching in software-defined metro IP over optical networks,” Opto-Electronics and Communications Conference (OECC), Shanghai, China, June 2015.
[Crossref]

Zhong, Z.

Z. Zhong, N. Hua, H. Li, Y. Li, and X. Zheng, “Considerations of effective tidal traffic dispatching in software-defined metro IP over optical networks,” Opto-Electronics and Communications Conference (OECC), Shanghai, China, June 2015.
[Crossref]

Comput. Commun. (1)

A. Ding and G. Poo, “A survey of optical multicast over WDM networks,” Comput. Commun. 26(2), 193–200 (2003).
[Crossref]

Comput. Netw. (1)

S. Azodolmolky, M. Klinkowski, E. Marin, D. Careglio, J. S. Pareta, and I. Tomkos, “A survey on physical layer impairments aware routing and wavelength assignment algorithms in optical networks,” Comput. Netw. 53(7), 926–944 (2009).
[Crossref]

IEEE Comm. Surv. and Tutor. (1)

N. Charbonneau and V. Vokkarane, “A survey of advance reservation routing and wavelength assignment in wavelength-routed WDM networks,” IEEE Comm. Surv. and Tutor. 14(4), 1037–1064 (2012).
[Crossref]

IEEE Trans. Wirel. Commun. (1)

R. Li, Z. Zhao, J. Zheng, C. Mei, Y. Cai, and H. Zhang, “The learning and prediction of application-level traffic data in cellular networks,” IEEE Trans. Wirel. Commun. 16(6), 3899–3912 (2017).
[Crossref]

Nature (2)

D. Silver, A. Huang, C. J. Maddison, A. Guez, L. Sifre, G. van den Driessche, J. Schrittwieser, I. Antonoglou, V. Panneershelvam, M. Lanctot, S. Dieleman, D. Grewe, J. Nham, N. Kalchbrenner, I. Sutskever, T. Lillicrap, M. Leach, K. Kavukcuoglu, T. Graepel, and D. Hassabis, “Mastering the game of Go with deep neural networks and tree search,” Nature 529(7587), 484–489 (2016).
[Crossref] [PubMed]

D. Silver, J. Schrittwieser, K. Simonyan, I. Antonoglou, A. Huang, A. Guez, T. Hubert, L. Baker, M. Lai, A. Bolton, Y. Chen, T. Lillicrap, F. Hui, L. Sifre, G. van den Driessche, T. Graepel, and D. Hassabis, “Mastering the game of Go without human knowledge,” Nature 550(7676), 354–359 (2017).
[Crossref] [PubMed]

Opt. Express (2)

Opt. Fiber Technol. (1)

H. Zhang, Y. Wang, H. Chen, Y. Zhao, and J. Zhang, “Exploring machine-learning-based control plane intrusion detection techniques in software defined optical networks,” Opt. Fiber Technol. 39, 37–42 (2017).
[Crossref]

Science (2)

M. I. Jordan and T. M. Mitchell, “Machine learning: Trends, perspectives, and prospects,” Science 349(6245), 255–260 (2015).
[Crossref] [PubMed]

C. Song, Z. Qu, N. Blumm, and A. L. Barabási, “Limits of predictability in human mobility,” Science 327(5968), 1018–1021 (2010).
[Crossref] [PubMed]

Telecommunications Science (1)

Y. Ji, J. Zhang, and Y. Zhao, “Development prospects of software defined optical networks,” Telecommunications Science 30(8), 19–22 (2014).

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K. He, X. Zhang, S. Ren, and J. Sun, “Deep residual learning for image recognition,” Proceedings of the IEEE conference on computer vision and pattern recognition, Boston, Massachusetts, USA, June 2015.

C. Szegedy, S. Ioffe, V. Vanhoucke, and A. A. Alemi, “Inception-v4, inception-ResNet and the impact of residual connections on learning,” Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17), San Francisco, California, USA, Feb. 2017.

S. Troia, G. Sheng, R. Alvizu, G. A. Maier, and A. Pattavina, “Identification of tidal-traffic patterns in metro-area mobile networks via matrix factorization based model,” IEEE International Conference on Pervasive Computing and Communications, Kona, USA, May 2017.
[Crossref]

Z. Zhong, N. Hua, H. Li, Y. Li, and X. Zheng, “Considerations of effective tidal traffic dispatching in software-defined metro IP over optical networks,” Opto-Electronics and Communications Conference (OECC), Shanghai, China, June 2015.
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V. Mnih, A. P. Badia, M. Mirza, A. Graves, T. Harley, T. P. Lillicrap, D. Silver, and K. Kavukcuoglu, “Asynchronous methods for deep reinforcement learning,” Proceedings of the 33rd International Conference on Machine Learning, New York, NY, USA, 2016.

A. Krizhevsky, I. Sutskever, and G. E. Hinton, “ImageNet classification with deep convolutional neural networks,” NIPS Conference Proceedings, Lake Tahoe, Nevada, USA, December 2012.

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Figures (6)

Fig. 1
Fig. 1 The evolution of intelligent optical networks.
Fig. 2
Fig. 2 Architecture of SOON.
Fig. 3
Fig. 3 Procedure and result of traffic prediction, (a) IP-over-WDM scene, (b) ANN training, (c) traffic prediction, (d) traffic adjustment.
Fig. 4
Fig. 4 Demonstration of alarm prediction in SOON, (a) alarm report, (b) ML model generation, (c) IN_PWR_LOW alarm prediction.
Fig. 5
Fig. 5 Demonstration of anomaly action detection, (a) scene, (b) service requirements classification, (c) detection rate.
Fig. 6
Fig. 6 Routing and wavelength assignment via ML, (a) multi-modal learning, (b) performance of multi-modal reinforcement learning model.

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