Service Function Chain Deployment Algorithm Based on Double Deep Q Network

Abstract

To achieve the minimum resource cost of service function chain deployment under the dynamic changes of the substrate network resources and the high dimension of the network model, this paper proposes a service function chain deployment algorithm based on a double deep Q network. Firstly, according to the characteristics that the substrate network resources change dynamically with the arrival of the service function chain, the deployment of the service function chain is converted into a Markov decision process. Then, the resource cost is used as the reward function, and finally, the service function chain is solved using the double deep Q network algorithm. Dynamically arriving at optimal deployment strategy. The simulation results show that the algorithm can effectively improve the request acceptance rate and reduce the average deployment cost and delay.