{"title":"基于深度强化学习的EONs组播会话自适应重构(特邀论文)","authors":"Xiaojian Tian, Baojia Li, Zuqing Zhu","doi":"10.1109/ICOCN53177.2021.9563729","DOIUrl":null,"url":null,"abstract":"We proposed a deep reinforcement learning (DRL) based approach to reconfigure the multicast sessions in an elastic optical network (EON) adaptively. Simulation results demonstrate that our proposal maintains the optimality of light-trees with less reconfigurations and reduces blocking probability.","PeriodicalId":6756,"journal":{"name":"2021 19th International Conference on Optical Communications and Networks (ICOCN)","volume":"1 1","pages":"1-3"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Reconfiguring Multicast Sessions in EONs Adaptively with Deep Reinforcement Learning: (Invited Paper)\",\"authors\":\"Xiaojian Tian, Baojia Li, Zuqing Zhu\",\"doi\":\"10.1109/ICOCN53177.2021.9563729\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We proposed a deep reinforcement learning (DRL) based approach to reconfigure the multicast sessions in an elastic optical network (EON) adaptively. Simulation results demonstrate that our proposal maintains the optimality of light-trees with less reconfigurations and reduces blocking probability.\",\"PeriodicalId\":6756,\"journal\":{\"name\":\"2021 19th International Conference on Optical Communications and Networks (ICOCN)\",\"volume\":\"1 1\",\"pages\":\"1-3\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-08-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 19th International Conference on Optical Communications and Networks (ICOCN)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICOCN53177.2021.9563729\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 19th International Conference on Optical Communications and Networks (ICOCN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOCN53177.2021.9563729","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Reconfiguring Multicast Sessions in EONs Adaptively with Deep Reinforcement Learning: (Invited Paper)
We proposed a deep reinforcement learning (DRL) based approach to reconfigure the multicast sessions in an elastic optical network (EON) adaptively. Simulation results demonstrate that our proposal maintains the optimality of light-trees with less reconfigurations and reduces blocking probability.
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