Service chain mapping algorithm based on reinforcement learning - Liang WEI; Tao HUANG; Jiao ZHANG; Zenan WANG; Jiang LIU; Yunjie LIU (Tongxin xuebao)
A service chain resource scheduling architecture of multi-agent based on artificial intelligence technology was proposed.Meanwhile,a service chain mapping algorithm based on reinforcement learning was designed.Through the Q-learning mechanism,the location of each virtual network element in the service chain was determined according to the system status and the reward and punishment feedback after the deployment.The experimental results show that compared with the classical algorithms,the algorithm effectively reduces the average transmission delay of the service and improves the load balance of the system.