SFC Consolidation: Energy-aware SFC Management using Deep Reinforcement Learning

Networks are becoming more complex, and there’s a growing focus on making them more flexible. To meet this need, Network Functions Virtualization (NFV) has been introduced. Accordingly, efficient scheduling for Virtual Network Functions (VNFs) and Service Function Chains (SFCs) is highlighted. Many research about SFC scheduling focus on deploying new SFC. However, during off-peak times, like early morning hours, it’s essential to reorganize existing SFCs to cut down on power usage. This study propose reorganization method that not only reduce power consumption, but also maintain or improve service performance (especially, we try to reduce service latency). To achieve this, we integrated VM consolidation, a strategy from Cloud Data Centers, with SFC scheduling. We also utilized a Deep Reinforcement Learning technique called Rainbow, and Self-Attention Mechanism. Consequently, our approach resulted in improved performance compared to other rule-based methods.