• Optical Communication Technology
  • Vol. 44, Issue 6, 46 (2020)
WANG Ya'nan1, YANG Xue2, ZHUANG Haotao3, ZHU Min2..., KANG Le2 and ZHAO Yongli3|Show fewer author(s)
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
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    DOI: 10.13921/j.cnki.issn1002-5561.2020.06.011 Cite this Article
    WANG Ya'nan, YANG Xue, ZHUANG Haotao, ZHU Min, KANG Le, ZHAO Yongli. Algorithm of logical topology mapping for resource optimization based on reinforcement learning[J]. Optical Communication Technology, 2020, 44(6): 46 Copy Citation Text show less

    Abstract

    The optical node wavelength multiplexer / demultiplexer and optical switch matrix in optical transport network(OTN) can map the logical topology of any structure on the physical topology, the unreasonable mapping scheme will consume additional port resources. A logic topology optimization mapping algorithm based on reinforcement learning(RL) is proposed. The preprocessed topological state and logical channel data are used to train the RL model, so as to allocate the global wavelength resources to the logical channel, and finally achieve the purpose of resource optimization. Simulation results show that the proposed algorithm can effectively reduce the resource consumption in the process of logical topology mapping, thus minimizing the cost of network deployment.
    WANG Ya'nan, YANG Xue, ZHUANG Haotao, ZHU Min, KANG Le, ZHAO Yongli. Algorithm of logical topology mapping for resource optimization based on reinforcement learning[J]. Optical Communication Technology, 2020, 44(6): 46
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