Reliability deployment of service function chain based on multi-agent reinforcement learning

In order to overcome the shortcomings of traditional networks, Network Function Virtualization (NFV) is widely used. For meeting the diverse service needs of users, the deployment of service function chain based on NFV has become a current research focus. In the actual scenario that the network service may be interrupted due to the failure of the physical server, this paper proposes a noval reliable deployment method of service function chain based on multi-agent reinforcement learning. Firstly, an integer linear programming (ILP) model is established for the reliable deployment problem of service function chain. Secondly, an efficient MADDPG algorithm is designed to solve it. The experimental results show that the proposed algorithm reduces the cost of physical node computing resources and link bandwidth resources, and improves the acceptance rate of network service requests under satisfying reliability constraints with compared algorithm.