In order to solve the high-dimensional Service Function Chain(SFC)deployment problem of high reliability and low cost in the Network Function Virtualization(NFV)environment,an Improving Service and Reducing Consumption based on Proximal Policy Optimization(PPO-ISRC)is proposed.Firstly,considering the characteristics of the underlying physical server and SFC,the state transition process of the underlying server network is descried,and the deployment of SFC is taken as a Markov Decision Process.Then the reward function is set with the optimization goal of maximizing the service rate and minimizing resource consumption.Finally the PPO method is used to solve the SFC deployment strategy.The results show that compared with the heuristic algorithm First-Fit Dijkstra(FFD)and the Deep Deterministic Policy Gradient(DDPG)algorithm,the proposed algorithm has the characteristics of fast convergence speed and higher stability.Under the requirements of service quality,the deployment cost is reduced and the reliability of network service is improved.
关键词
网络功能虚拟化/服务功能链/深度强化学习/近端策略优化
Key words
Network Function Virtualization(NFV)/Service Function Chain(SFC)/Deep Reinforcement Learning(DRL)/Proximal Policy Optimization(PPO)
维普
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