Research on Reliable Deployment Algorithm for Service Function Chain Based on Deep Reinforcement Learning

This paper investigates the reliable deployment algorithm for Service Function Chains (SFC) based on deep reinforcement learning. SFC, as a chained function composition for complex network services, plays a crucial role in improving network efficiency and stability. To address the issue of existing SFC deployment algorithms that overlook the reliability of network functions and links, this paper proposes a deep reinforcement learning-based algorithm that utilizes a virtual network function and virtual link reliability mapping model for optimization. By learning the mapping between system states and actions, the algorithm can optimize the deployment strategy of SFC, thereby enhancing its reliability and performance. Experimental results demonstrate that the proposed algorithm can significantly improve the reliability of SFC and have practical implications for network service deployment.