Cross-Domain Service Function Chain Routing: Multiagent Reinforcement Learning Approaches

Abstract

The service function chain (SFC) routing has been increasingly associated with multi-domain networks. However, several multi-domain SFC routing issues, linked to cross-domain interactions and emphasized by the heterogeneity of substrate topologies and administrative authorities, present a challenge. We propose the Cooperative Multi-agent Reinforcement Learning (CMRL) based algorithm for multi-domain SFC routing problem. Simulations on the real-world network topology demonstrate that our proposal can provide more than two and four times reduction in terms of the run time and network resource cost, respectively.