Online Service Function Chain Deployment Method Based on Deep Q Network

被引:6
|
作者
Qiu Hang [1 ]
Tang Hongbo [1 ]
You Wei [1 ]
机构
[1] Univ Peoples Liberat Army Strateg Support Force, Informat Engn, Zhengzhou 450002, Peoples R China
基金
中国国家自然科学基金;
关键词
Network function virtualization; Service function chain; Markov decision process; Deep Q network; OPTIMIZATION; PLACEMENT;
D O I
10.11999/JEIT201009
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
To deal with the dynamic nature of 5G network resource state and the difficulty of service function chain deployment under the high- dimensional network state model, an online Service function Chain Deployment method based on Deep Q network (DeePSCD) is proposed. First, to describe the dynamic nature of network resource state, the service function chain deployment is modeled as a Markov decision process. Then, the deep Q network is used to solve the online service function chain deployment problem in the high-dimensional system resource model. This method can effectively describe the dynamic changes of network resource state. Specifically, deep Q network handles the complexity of problem and determines the optimal deployment solution of service function chain. Simulation results show that the proposed method can reduce the deployment cost of the service function chain and increase the acceptance rate while meeting the service delay constraint.
引用
收藏
页码:3122 / 3130
页数:9
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