Jiahua Gu, M. Zhu, Yunwu Wang, Xiaofeng Cai, Y. Cai, Jiao Zhang
{"title":"启发式辅助深度强化学习在弹性城域聚合光网络中实现资源高效和qos保证的5G RAN片迁移","authors":"Jiahua Gu, M. Zhu, Yunwu Wang, Xiaofeng Cai, Y. Cai, Jiao Zhang","doi":"10.23919/OFC49934.2023.10117262","DOIUrl":null,"url":null,"abstract":"We propose a heuristic-assisted deep reinforcement learning framework for resource-efficient and QoS-guaranteed 5G RAN slice migration in EONs, which can optimize the spectrum resource consumption, traffic migration, and power consumption, simultaneously.","PeriodicalId":355445,"journal":{"name":"2023 Optical Fiber Communications Conference and Exhibition (OFC)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Heuristic-assisted Deep Reinforcement Learning for Resource-efficient and QoS-guaranteed 5G RAN Slice Migration in Elastic Metro Aggregation Optical Networks\",\"authors\":\"Jiahua Gu, M. Zhu, Yunwu Wang, Xiaofeng Cai, Y. Cai, Jiao Zhang\",\"doi\":\"10.23919/OFC49934.2023.10117262\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose a heuristic-assisted deep reinforcement learning framework for resource-efficient and QoS-guaranteed 5G RAN slice migration in EONs, which can optimize the spectrum resource consumption, traffic migration, and power consumption, simultaneously.\",\"PeriodicalId\":355445,\"journal\":{\"name\":\"2023 Optical Fiber Communications Conference and Exhibition (OFC)\",\"volume\":\"69 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 Optical Fiber Communications Conference and Exhibition (OFC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/OFC49934.2023.10117262\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 Optical Fiber Communications Conference and Exhibition (OFC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/OFC49934.2023.10117262","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Heuristic-assisted Deep Reinforcement Learning for Resource-efficient and QoS-guaranteed 5G RAN Slice Migration in Elastic Metro Aggregation Optical Networks
We propose a heuristic-assisted deep reinforcement learning framework for resource-efficient and QoS-guaranteed 5G RAN slice migration in EONs, which can optimize the spectrum resource consumption, traffic migration, and power consumption, simultaneously.
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