SDN Lullaby: VM Consolidation for SDN using Transformer-Based Deep Reinforcement Learning

This study introduces Virtual Machine (VM) Consolidation using a Transformer-based Deep Reinforcement Learning (DRL) method, to address the complexity and inefficiency in operating Software Defined Networks-enabled Network Function Virtualization (SDN-enabled NFV). The distribution of Virtual Network Functions (VNFs) as VMs across servers often leads to energy loss due to irregular deployment. The proposed approach enhances energy efficiency while maintaining the performance of Service Function Chains (SFCs). By refining the VM consolidation process and leveraging a more sophisticated DRL method, this approach promises a more efficient solution to VM consolidation in SDN-enabled NFV environments.