典型文献
Reinforced virtual optical network embedding algorithm in EONs for edge computing
文献摘要：
As the core technology of optical networks virtualization,virtual optical network embedding(VONE)enables multiple virtual network requests to share substrate elastic optical network(EON)resources simultaneously and hence has been applicated in edge computing scenarios.In this paper,we propose a reinforced virtual optical network embedding(R-VONE)algorithm based on deep reinforcement learning(DRL)to optimize network embedding policies automatically.The network resource attributes are extracted as the environment state for model training,based on which DRL agent can deduce the node embedding probability.Experimental results indicate that R-VONE presents a significant advantage with lower blocking probability and higher resource utilization.
文献关键词：
中图分类号：
作者姓名：
Zhu Ruijie;Li Gong;Wang Peisen;Zhang Wenchao
作者机构：
School of Computer and Artificial Intelligence,Zhengzhou University,Zhengzhou 450001,China;Henan Institute of Advanced Technology,Zhengzhou University,Zhengzhou 450002,China
文献出处：
引用格式：
[1]Zhu Ruijie;Li Gong;Wang Peisen;Zhang Wenchao-.Reinforced virtual optical network embedding algorithm in EONs for edge computing)[J].中国邮电高校学报（英文版）,2022(06):18-29
A类：
EONs,VONE,applicated
B类：
Reinforced,optical,embedding,algorithm,edge,computing,core,technology,networks,virtualization,enables,multiple,requests,share,substrate,elastic,resources,simultaneously,hence,has,been,scenarios,In,this,paper,propose,reinforced,deep,reinforcement,learning,DRL,optimize,policies,automatically,attributes,extracted,environment,state,model,training,which,agent,deduce,node,probability,Experimental,results,indicate,that,presents,significant,advantage,lower,blocking,higher,utilization
AB值：
0.530244
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机标中图分类号，由域田数据科技根据网络公开资料自动分析生成，仅供学习研究参考。
