Algoritmo Baseado em Aprendizado de Máquina para Alocação de Núcleo em Redes Ópticas Elásticas com Multiplexação Espacial
Abstract
Spatial division multiplexing elastic optical networks (SDM-EON) using multicore fibers (MCF) are promising candidates for the future transport networks. In MCFs, a new dimension is added to the resource allocation problem: core allocation. In this paper, a machine learning algorithm for core allocation (AMN) in SDM-EONs is proposed. Compared with other solutions in the literature and a scenario with a low crosstalk level, AMN achieves at least 25.35% gain in terms of request blocking probability (RBP) and at least 24.81% for blocked data ratio (BDR). In a scenario with a high crosstalk level, AMN achieves at least 8.16% gain for RBP and at least 9.28% for BDR.
References
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Yao, Q., Yang, H., Zhu, R., Yu, A., Bai, W., Tan, Y., Zhang, J., and Xiao, H. (2018). Core, mode, and spectrum assignment based on machine learning in space division multiplexing elastic optical networks. IEEE Access, 6:15898–15907.
Zhang, Y., Xin, J., Li, X., and Huang, S. (2020). Overview on routing and resource allocation based machine learning in optical networks. Optical Fiber Technology, 60:102355.
Zhao, J., Wymeersch, H., and Agrell, E. (2015). Nonlinear impairment-aware static resource allocation in elastic optical networks. IEEE/OSA Journal of Lightwave Technology, 33(22):4554–4564.
Beyranvand, H. and Salehi, J. (2013). A quality-of-transmission aware dynamic routing and spectrum assignment scheme for future elastic optical networks. IEEE/OSA Journal of Lightwave Technology, 31(18):3043–3054.
Brasileiro, I., Costa, L., and Drummond, A. (2020). A survey on challenges of spatial division multiplexing enabled elastic optical networks. Optical Switching and Networking, 38:100584.
Carena, A., Bosco, G., Curri, V., Jiang, Y., Poggiolini, P., and Forghieri, F. (2014). EGN model of non-linear fiber propagation. Optics Express, 22(13):16335–16362.
Dijkstra, E. (1959). A note on two problems in connexion with graphs, volume 1. Numerische Mathematik.
Fontinele, A., Santos, I., Neto, J. N., Campelo, D. R., and Soares, A. (2017). An efficient IA-RMLSA algorithm for transparent elastic optical networks. Computer Networks, 118:1–14.
Fujii, S., Hirota, Y., Tode, H., and Murakami, K. (2014). On-demand spectrum and core allocation for reducing crosstalk in multicore fibers in elastic optical networks. IEEE/OSA Journal of Optical Communications and Networking, 6(12):1059–1071.
Gao, G., Zhang, J., Wang, L., Gu, W., and Ji, Y. (2014). Influence of physical layer configuration on performance of elastic optical OFDM networks. IEEE Communications Letters, 18(4):672–675.
Gong, L., Zhou, X., Liu, X., Zhao, W., Lu, W., and Zhu, Z. (2013). Efficient resource allocation for all-optical multicasting over spectrum-sliced elastic optical networks. IEEE/OSA Journal of Optical Communications and Networking, 5(8):836–847.
Habibi, M. and Beyranvand, H. (2019). Impairment-aware manycast routing, modulation level, and spectrum assignment in elastic optical networks. IEEE/OSA Journal of Optical Communications and Networking, 11(5):179–189.
Hayashi, T., Taru, T., Shimakawa, O., Sasaki, T., and Sasaoka, E. (2011). Design and fabrication of ultra-low crosstalk and low-loss multi-core fiber. Optics Express, 19:16576–16592.
ITU-T G.694.1 (2020). Spectral grids for WDM applications: DWDM frequency grid. Standard, International Telecommunication Union ITU.
Ives, D., Bayvel, P., and Savory, S. (2015). Routing, modulation, spectrum and launch power assignment to maximize the traffic throughput of a nonlinear optical mesh network. Photonic Network Communications, 29(3):244–256.
Klinkowski, M., Ksieniewicz, P., Jaworski, M., Zalewski, G., and Walkowiak, K. (2020). Machine learning assisted optimization of dynamic crosstalk-aware spectrally-spatially flexible optical networks. IEEE/OSA Journal of Lightwave Technology, 38(7):1625–1635.
Klinkowski, M. and Zalewski, G. (2019). Dynamic crosstalk-aware lightpath provisioning in spectrally-spatially flexible optical networks. IEEE/OSA Journal of Optical Communications and Networking, 11(5):213–225.
Lacerda Jr, J., Cartaxo, A., and Soares, A. (2021). New core and spectrum balancing algorithms for space division multiplexed elastic optical networks. In 2021 IEEE International Mediterranean Conference on Communications and Networking (MeditCom) (IEEE MeditCom 2021), pages 383–388, Athens, Greece.
LeCun, Y., Bengio, Y., and Hinton, G. (2015). Deep learning. Nature (London), 521(7553):436–444.
Lobato, F. R., Jacob, A., Rodrigues, J., Cartaxo, A. V., and Costa, J. (2019). Inter-core crosstalk aware greedy algorithm for spectrum and core assignment in space division multiplexed elastic optical networks. Optical Switching and Networking, 33:61–73.
Moghaddam, E. E., Beyranvand, H., and Salehi, J. A. (2020). Crosstalk-aware resource allocation in survivable space-division-multiplexed elastic optical networks supporting hybrid dedicated and shared path protection. IEEE/OSA Journal of Lightwave Technology, 38(6):1095–1102.
Monteiro, N., Junior, W., Fontinele, A., Campelo, D., Paiva, A., Rabêlo, R., and Soares, A. (2020). Alocação de banda de guarda adaptativa utilizando redes neurais multilayer perceptron em redes ópticas elásticas. In Anais do XXXVIII Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos, pages 770–783, Rio de Janeiro-RJ.
Muhammad, A., Zervas, G., and Forchheimer, R. (2015). Resource allocation for space-division multiplexing: optical white box versus optical black box networking. IEEE/OSA Journal of Lightwave Technology, 33(23):4928–4941.
Poggiolini, P. and Jiang, Y. (2017). Recent advances in the modeling of the impact of nonlinear fiber propagation effects on uncompensated coherent transmission systems. IEEE/OSA Journal of Lightwave Technology, 35(3):458–480.
Tanenbaum, A. S. and Wetherall, D. (2011). Redes de computadores: 5ª edição. Pearson Prentice Hall.
Yaghubi-Namaad, M., Rahbar, A. G., and Alizadeh, B. (2018). Adaptive modulation and flexible resource allocation in space division multiplexed elastic optical networks. IEEE/OSA Journal of Optical Communications and Networking, 10(3):240–251.
Yan, L., Agrell, E., Wymeersch, H., Johannisson, P., Di Taranto, R., and Brandt-Pearce, M. (2015). Link-level resource allocation for flexible-grid nonlinear fiber-optic communication systems. IEEE Photonics Technology Letters, 27(12):1250–1253.
Yao, Q., Yang, H., Zhu, R., Yu, A., Bai, W., Tan, Y., Zhang, J., and Xiao, H. (2018). Core, mode, and spectrum assignment based on machine learning in space division multiplexing elastic optical networks. IEEE Access, 6:15898–15907.
Zhang, Y., Xin, J., Li, X., and Huang, S. (2020). Overview on routing and resource allocation based machine learning in optical networks. Optical Fiber Technology, 60:102355.
Zhao, J., Wymeersch, H., and Agrell, E. (2015). Nonlinear impairment-aware static resource allocation in elastic optical networks. IEEE/OSA Journal of Lightwave Technology, 33(22):4554–4564.
Published
2022-05-23
How to Cite
LACERDA JR, Jurandir C.; CARTAXO, Adolfo V. T.; SOARES, André C. B..
Algoritmo Baseado em Aprendizado de Máquina para Alocação de Núcleo em Redes Ópticas Elásticas com Multiplexação Espacial. In: BRAZILIAN SYMPOSIUM ON COMPUTER NETWORKS AND DISTRIBUTED SYSTEMS (SBRC), 40. , 2022, Fortaleza.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2022
.
p. 70-83.
ISSN 2177-9384.
DOI: https://doi.org/10.5753/sbrc.2022.221965.
