Abstract

Integrating quantum key distribution (QKD) with existing optical networks is highly desired to reduce the deployment costs and achieve efficient resource utilization, and some point-to-point transmitting experiments have verified its feasibility. Nevertheless, there are still many problems in the realistic scenario where QKD coexists with dynamic data traffics. On the one hand, the conventional static channel allocation schemes cannot guarantee the quality of quantum channels in the presence of the time-varying noises. On the other hand, considering the complex noise generation caused by dynamic classical data traffics with variable characters, it is challenging to achieve online high-performance quantum channel assignments. To address these problems, we propose a machine learning based noise-suppressing channel allocation (ML-NSCA) scheme. In this scheme, the LightGBM based ML framework is trained to predict the optimal channel allocations with lowest noise impacts, according to which, the quantum channels are periodically reallocated to guarantee high secure key rate. To improve the accuracy and scalability of the ML framework, we also optimize the method of feature extraction during the training process. The performance evaluation results indicate that the proposed scheme can effectively resist the dynamic noise impacts in the realistic optical networks and obtain higher secure key rate with less operation complexity than the previous schemes.

© 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

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References

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2019 (1)

S. Wang, D.-Y. He, Z.-Q. Yin, F.-Y. Lu, C.-H. Cui, W. Chen, Z. Zhou, G.-C. Guo, and Z.-F. Han, “Beating the fundamental rate-distance limit in a proof-of-principle quantum key distribution system,” Phys. Rev. X 9, 021046 (2019).
[Crossref]

2018 (12)

Q. Zhang, F. Xu, Y.-A. Chen, C.-Z. Peng, and J.-W. Pan, “Large scale quantum key distribution: challenges and solutions,” Opt. Express 26(18), 24260–24273 (2018).
[Crossref]

Y. Mao, B.-X. Wang, C. Zhao, G. Wang, R. Wang, H. Wang, F. Zhou, J. Nie, Q. Chen, Y. Zhao, Q. Zhang, J. Zhang, T.-Y. Chen, and J.-W. Pan, “Integrating quantum key distribution with classical communications in backbone fiber network,” Opt. Express 26(5), 6010–6020 (2018).
[Crossref]

Y. Ji, J. Zhang, X. Wang, and H. Yu, “Towards converged, collaborative and co-automatic (3c) optical networks,” Sci. China Inf. Sci. 61(12), 121301 (2018).
[Crossref]

Z.-Q. Yin, S. Wang, W. Chen, Y.-G. Han, R. Wang, G.-C. Guo, and Z.-F. Han, “Improved security bound for the round-robin-differential-phase-shift quantum key distribution,” Nat. Commun. 9(1), 457 (2018).
[Crossref]

Z. Yuan, A. Plews, R. Takahashi, K. Doi, W. Tam, A. Sharpe, A. Dixon, E. Lavelle, J. Dynes, A. Murakami, M. Kujiraoka, M. Lucamarini, Y. Tanizawa, H. Sato, and A. J. Shields, “10-Mb/s quantum key distribution,” J. Lightwave Technol. 36(16), 3427–3433 (2018).
[Crossref]

A. Boaron, G. Boso, D. Rusca, C. Vulliez, C. Autebert, M. Caloz, M. Perrenoud, G. Gras, F. Bussières, M.-J. Li, D. Nolan, and A. Martin, “Secure quantum key distribution over 421 km of optical fiber,” Phys. Rev. Lett. 121(19), 190502 (2018).
[Crossref]

M. Lucamarini, Z. L. Yuan, J. F. Dynes, and A. J. Shields, “Overcoming the rate–distance limit of quantum key distribution without quantum repeaters,” Nature 557(7705), 400–403 (2018).
[Crossref]

S. Bahrani, M. Razavi, and J. A. Salehi, “Wavelength assignment in hybrid quantum-classical networks,” Sci. Rep. 8(1), 3456 (2018).
[Crossref]

J. Niu, Y. Sun, C. Cai, and Y. Ji, “Optimized channel allocation scheme for jointly reducing four-wave mixing and raman scattering in the DWDM-QKD system,” Appl. Opt. 57(27), 7987–7996 (2018).
[Crossref]

C. Rottondi, L. Barletta, A. Giusti, and M. Tornatore, “Machine-learning method for quality of transmission prediction of unestablished lightpaths,” IEEE/OSA J. Opt. Commun. Netw. 10(2), A286–A297 (2018).
[Crossref]

Q. Yao, H. Yang, R. Zhu, A. Yu, W. Bai, Y. Tan, J. Zhang, and H. Xiao, “Core, mode, and spectrum assignment based on machine learning in space division multiplexing elastic optical networks,” IEEE Access 6, 15898–15907 (2018).
[Crossref]

Y. Cao, Y. Zhao, Y. Wu, X. Yu, and J. Zhang, “Time-scheduled quantum key distribution (QKD) over wdm networks,” J. Lightwave Technol. 36(16), 3382–3395 (2018).
[Crossref]

2017 (3)

2016 (3)

H. L. Yin, T. Y. Chen, Z. W. Yu, H. Liu, L. X. You, Y. H. Zhou, S. J. Chen, Y. Mao, M. Q. Huang, W. J. Zhang, H. Chen, M. J. Li, D. Nolan, F. Zhou, X. Jiang, Z. Wang, Q. Zhang, X. B. Wang, and J. W. Pan, “Measurement-device-independent quantum key distribution over a 404 km optical fiber,” Phys. Rev. Lett. 117(19), 190501 (2016).
[Crossref]

Y. Sun, Y. Lu, J. Niu, and Y. Ji, “Reduction of FWM noise in WDM-based QKD systems using interleaved and unequally spaced channels,” Chin. Opt. Lett. 14(6), 060602 (2016).
[Crossref]

J. F. Dynes, W. W. Tam, A. Plews, B. Fröhlich, A. W. Sharpe, M. Lucamarini, Z. Yuan, C. Radig, A. Straw, T. Edwards, and A. J. Shields, “Ultra-high bandwidth quantum secured data transmission,” Sci. Rep. 6(1), 35149 (2016).
[Crossref]

2015 (1)

L.-J. Wang, L.-K. Chen, L. Ju, M.-L. Xu, Y. Zhao, K. Chen, Z.-B. Chen, T.-Y. Chen, and J.-W. Pan, “Experimental multiplexing of quantum key distribution with classical optical communication,” Appl. Phys. Lett. 106(8), 081108 (2015).
[Crossref]

2014 (5)

K. A. Patel, J. F. Dynes, M. Lucamarini, I. Choi, A. W. Sharpe, Z. L. Yuan, R. V. Penty, and A. J. Shields, “Quantum key distribution for 10 Gb/s dense wavelength division multiplexing networks,” Appl. Phys. Lett. 104(5), 051123 (2014).
[Crossref]

T. Ferreira Da Silva, G. B. Xavier, G. P. Temporao, and J. P. Von Der Weid, “Impact of Raman scattered noise from multiple telecom channels on fiber-optic quantum key distribution systems,” J. Lightwave Technol. 32(13), 2332–2339 (2014).
[Crossref]

R. Alléaume, C. Branciard, J. Bouda, T. Debuisschert, M. Dianati, N. Gisin, M. Godfrey, P. Grangier, T. Länger, N. Lütkenhaus, C. Monyk, P. Painchault, M. Peev, A. Poppe, T. Pornin, J. Rarity, J. Renner, G. Ribordy, M. Riguidel, L. Salvail, A. Shields, H. Weinfurter, and A. Zeilinger, “Using quantum key distribution for cryptographic purposes: a survey,” Theor. Comput. Sci. 560, 62–81 (2014).
[Crossref]

H.-K. Lo, M. Curty, and K. Tamaki, “Secure quantum key distribution,” Nat. Photonics 8(8), 595–604 (2014).
[Crossref]

J. Qiu, “Quantum communications leap out of the lab,” Nat. News 508(7497), 441–442 (2014).
[Crossref]

2010 (2)

P. Eraerds, N. Walenta, M. Legré, N. Gisin, and H. Zbinden, “Quantum key distribution and 1 Gbps data encryption over a single fibre,” New J. Phys. 12(6), 063027 (2010).
[Crossref]

I. Choi, R. J. Young, and P. D. Townsend, “Quantum key distribution on a 10Gb/s WDM-PON,” Opt. Express 18(9), 9600–9612 (2010).
[Crossref]

2009 (2)

W. Maeda, A. Tanaka, S. Takahashi, A. Tajima, and A. Tomita, “Technologies for quantum key distribution networks integrated with optical communication networks,” IEEE J. Sel. Top. Quantum Electron. 15(6), 1591–1601 (2009).
[Crossref]

N. A. Peters, P. Toliver, T. E. Chapuran, R. J. Runser, S. R. McNown, C. G. Peterson, D. Rosenberg, N. Dallmann, R. J. Hughes, K. P. McCabe, J. E. Nordholt, and K. T. Tyagi, “Dense wavelength multiplexing of 1550 nm QKD with strong classical channels in reconfigurable networking environments,” New J. Phys. 11(4), 045012 (2009).
[Crossref]

2005 (2)

N. I. Nweke, P. Toliver, R. J. Runser, S. R. McNown, J. B. Khurgin, T. E. Chapuran, M. S. Goodman, R. J. Hughes, C. G. Peterson, K. McCabe, J. E. Nordholt, K. Tyagi, P. Hiskett, and N. Dallmann, “Experimental characterization of the separation between wavelength-multiplexed quantum and classical communication channels,” Appl. Phys. Lett. 87(17), 174103 (2005).
[Crossref]

X. Ma, B. Qi, Y. Zhao, and H.-K. Lo, “Practical decoy state for quantum key distribution,” Phys. Rev. A 72(1), 012326 (2005).
[Crossref]

2003 (1)

D. Gottesman, H. Lo, N. Lutkenhaus, and J. Preskill, “Security of quantum key distribution with imperfect devices,” Quantum Inf. Comput 4, 135 (2003).
[Crossref]

2000 (1)

H. Zang, J. P. Jue, and B. Mukherjee, “A review of routing and wavelength assignment approaches for wavelength-routed optical WDM networks,” SPIE/Baltzer Optical Network Mag. 1, 47–60 (2000).

1999 (1)

H.-K. Lo and H. F. Chau, “Unconditional security of quantum key distribution over arbitrarily long distances,” Science 283(5410), 2050–2056 (1999).
[Crossref]

1997 (1)

P. Townsend, “Simultaneous quantum cryptographic key distribution and conventional data transmission over installed fibre using wavelength-division multiplexing,” Electron. Lett. 33(3), 188–190 (1997).
[Crossref]

1982 (1)

W. K. Wootters and W. H. Zurek, “A single quantum cannot be cloned,” Nature 299(5886), 802–803 (1982).
[Crossref]

Alber, G.

M. Geihs, O. Nikiforov, D. Demirel, A. Sauer, D. Butin, F. Günther, G. Alber, T. Walther, and J. Buchmann, “The status of quantum-key-distribution-based long-term secure internet communication,” IEEE Transactions on Sustainable Computing (to be published).

Aleksic, S.

S. Aleksic, D. Winkler, F. Hipp, A. Poppe, G. Franzl, and B. Schrenk, “Towards a smooth integration of quantum key distribution in metro networks,” in Proceedings of 16th International Conference on Transparent Optical Networks (ICTON 2014), (IEEE, 2014), paper Tu.B1.1.

Alléaume, R.

R. Alléaume, C. Branciard, J. Bouda, T. Debuisschert, M. Dianati, N. Gisin, M. Godfrey, P. Grangier, T. Länger, N. Lütkenhaus, C. Monyk, P. Painchault, M. Peev, A. Poppe, T. Pornin, J. Rarity, J. Renner, G. Ribordy, M. Riguidel, L. Salvail, A. Shields, H. Weinfurter, and A. Zeilinger, “Using quantum key distribution for cryptographic purposes: a survey,” Theor. Comput. Sci. 560, 62–81 (2014).
[Crossref]

Amar, D.

P. Samadi, D. Amar, C. Lepers, M. Lourdiane, and K. Bergman, “Quality of transmission prediction with machine learning for dynamic operation of optical WDM networks,” in Proceedings of 2017 European Conference on Optical Communication (ECOC), (IEEE, 2017), paper W3A1.

Autebert, C.

A. Boaron, G. Boso, D. Rusca, C. Vulliez, C. Autebert, M. Caloz, M. Perrenoud, G. Gras, F. Bussières, M.-J. Li, D. Nolan, and A. Martin, “Secure quantum key distribution over 421 km of optical fiber,” Phys. Rev. Lett. 121(19), 190502 (2018).
[Crossref]

Bahrani, S.

S. Bahrani, M. Razavi, and J. A. Salehi, “Wavelength assignment in hybrid quantum-classical networks,” Sci. Rep. 8(1), 3456 (2018).
[Crossref]

Bai, W.

Q. Yao, H. Yang, R. Zhu, A. Yu, W. Bai, Y. Tan, J. Zhang, and H. Xiao, “Core, mode, and spectrum assignment based on machine learning in space division multiplexing elastic optical networks,” IEEE Access 6, 15898–15907 (2018).
[Crossref]

Barletta, L.

C. Rottondi, L. Barletta, A. Giusti, and M. Tornatore, “Machine-learning method for quality of transmission prediction of unestablished lightpaths,” IEEE/OSA J. Opt. Commun. Netw. 10(2), A286–A297 (2018).
[Crossref]

Bergman, K.

P. Samadi, D. Amar, C. Lepers, M. Lourdiane, and K. Bergman, “Quality of transmission prediction with machine learning for dynamic operation of optical WDM networks,” in Proceedings of 2017 European Conference on Optical Communication (ECOC), (IEEE, 2017), paper W3A1.

Bi, Y.

Y. Ou, E. Hugues-Salas, F. Ntavou, R. Wang, Y. Bi, S. Yan, G. Kanellos, R. Nejabati, and D. Simeonidou, “Field-trial of machine learning-assisted quantum key distribution (QKD) networking with SDN,” in Proceedings of 2018 European Conference on Optical Communication (ECOC), (IEEE, 2018), paper Mo3D.

Boaron, A.

A. Boaron, G. Boso, D. Rusca, C. Vulliez, C. Autebert, M. Caloz, M. Perrenoud, G. Gras, F. Bussières, M.-J. Li, D. Nolan, and A. Martin, “Secure quantum key distribution over 421 km of optical fiber,” Phys. Rev. Lett. 121(19), 190502 (2018).
[Crossref]

Boso, G.

A. Boaron, G. Boso, D. Rusca, C. Vulliez, C. Autebert, M. Caloz, M. Perrenoud, G. Gras, F. Bussières, M.-J. Li, D. Nolan, and A. Martin, “Secure quantum key distribution over 421 km of optical fiber,” Phys. Rev. Lett. 121(19), 190502 (2018).
[Crossref]

Bouda, J.

R. Alléaume, C. Branciard, J. Bouda, T. Debuisschert, M. Dianati, N. Gisin, M. Godfrey, P. Grangier, T. Länger, N. Lütkenhaus, C. Monyk, P. Painchault, M. Peev, A. Poppe, T. Pornin, J. Rarity, J. Renner, G. Ribordy, M. Riguidel, L. Salvail, A. Shields, H. Weinfurter, and A. Zeilinger, “Using quantum key distribution for cryptographic purposes: a survey,” Theor. Comput. Sci. 560, 62–81 (2014).
[Crossref]

Branciard, C.

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Figures (10)

Fig. 1.
Fig. 1. (a) Configuration of the DWDM-QKD network; MUX-Link: the link in which quantum signals and classical signals are multiplexed; Dch-Link: the link that only transmits the classical data signals. (b) Procedure of the trusted-relay-based key sharing, QM: quantum module.
Fig. 2.
Fig. 2. Illustration of the previous channel allocation schemes in the dyanmic DWDM-QKD network. (a) FBCA scheme; (b) PPCA scheme.
Fig. 3.
Fig. 3. Illustration of the ML-NSCA scheme.
Fig. 4.
Fig. 4. Procedure of the ML-based prediction of optimal Qch.
Fig. 5.
Fig. 5. The relative improtance of the features, and the values here are normalized by dividing the maximum value.
Fig. 6.
Fig. 6. Illustration of the lightpath establishment of data requests in the condition of wavelength continuity constraint; (a) the case that the third wavelength is available in all the three links; (b) the case that the fourth wavelength is available in all the three links.
Fig. 7.
Fig. 7. Network topology; (a) 6-node DWDM-QKD network; (b) 14-node DWDM-QKD network.
Fig. 8.
Fig. 8. Coincident rate in different subsets of test data.
Fig. 9.
Fig. 9. Evaluations of SKR in 4-node network; (a) SKR vs. data traffic load with $P_{Dch} =[-5, 5]$ dBm, TS=10 time slot; (b) SKR vs. configuration period with $P_{Dch} =[-5, 5]$ dBm, TL=10 Erlang; (c) SKR vs. fiber length of each link with TL=10 Erlang, TS=10 time slot, $P_{Dch} =[-5, 5]$ dBm; (d) SKR vs. number of Qchs with TL=10 Erlang, TS=10 time slot, $P_{Dch} =[-5, 5]$ dBm.
Fig. 10.
Fig. 10. SKR vs. data traffic load in 6-node network and 14-node network; (a) SKR vs. data traffic loads in 6-node network with $P_{Dch} =[-5, 5]$ dBm, TS=10 time slot; (b) SKR vs. data traffic loads in 14-node network with $P_{Dch} =[-5, 5]$ dBm, TS=10 time slot.

Tables (6)

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Table 1. Extracted feature subsets

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Table 2. RMSE comparision of different feature subsets

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Table 3. RMSE tested in the 6-node network and the 14-node network

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Table 4. Parameter settings of the ML module

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Table 5. Description of dividing the test datasets.

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Table 6. Major simulation parameters of DWDM-QKD system

Equations (2)

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R H T _ p a t h n = Maxmum :     R H T n m         ( m M ) ,
N o r _ T L m = p m Λ μ = p m T L ,

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