• Optical Communication Technology
  • Vol. 48, Issue 5, 46 (2024)
YU Tiankuo, YAO Qiuyan, YANG Hui, and GONG Shengye
Author Affiliations
  • State Key Laboratory of Information Photonics and Optical Communication, Beijing University of Posts and Telecommunications, Beijing 100876, China
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    DOI: 10.13921/j.cnki.issn1002-5561.2024.05.008 Cite this Article
    YU Tiankuo, YAO Qiuyan, YANG Hui, GONG Shengye. Optical network computing power scheduling method based on graph representation learning[J]. Optical Communication Technology, 2024, 48(5): 46 Copy Citation Text show less
    References

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    [4] ZHAO J, BAO B, YANG H, et al. Holding-time-and impairment-aware shared spectrum allocation in mixed-line-rate elastic optical networks [J]. Journal of Optical Communications and Networking, 2019,11(6): 322-332.

    [5] BAO B, YANG H, YAO Q, et al. Resource allocation with edge-cloud collaborative traffic prediction in integrated radio and optical networks[J]. IEEE Access, 2023, 11: 7067-7077.

    [6] YU T, YANG H, YAO Q, et al. Multi visual GRU based survivable computing power scheduling in metro optical networks[J]. IEEE Transactions on Network and Service Management, 2024,21(1):1302-1315.

    [7] BHATTI U A, TANG H, WU G, et al. Deep learning with graph convolutional networks: An overview and latest applications in computational intelligence[J]. International Journal of Intelligent Systems, 2023(3):1-28.

    [8] ULLAH I, MANZO M, SHAH M, et al. Graph convolutional networks: analysis, improvements and results[J]. Applied Intelligence, 2022, 52:1-12.

    [9] HADI M, PAKRAVAN M R, AGRELL E. Dynamic resource allocation in metro elastic optical networks using Lyapunov drift optimization [J]. Journal of Optical Communications and Networking, 2019,11(6): 250-259.

    YU Tiankuo, YAO Qiuyan, YANG Hui, GONG Shengye. Optical network computing power scheduling method based on graph representation learning[J]. Optical Communication Technology, 2024, 48(5): 46
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