With the emergence of$\mathbf{6 G}$, Inclusive Intelligent Services (IIS) are expected to become pervasive, requiring adaptive and efficient orchestration of diverse service functions. This work addresses the challenge of Service Function Chaining (SFC) provisioning in complex 6 G scenarios by proposing a hybrid framework that integrates Deep Reinforcement Learning (DRL) with a generative Conditional Variational Autoencoder (CVAE). The CVAE enhances feature representation and generalization, while the DRL agent leverages these latent features for optimized decision-making. Simulation results confirm that the proposed GenAI-SFC framework significantly outperforms state-of-the-art methods in terms of cost efficiency and end-to-end latency.

In the 6G vision, networks are expected to be more flexible in quickly solving network traffic scheduling issues and deploying services. Network Function Virtualization (NFV) is an innovative technology that involves extracting network functions from dedicated equipment to create Virtual Network Functions (VNFs). These VNFs are then chained together to form a Service Function Chain (SFC) that provides network service. However, there are still some issues with existing network service orchestration tools, such as unreasonable multi-traffic scheduling and additional programming requirements for end-users. We have developed a solution to address the challenges posed by data coupling and bandwidth preemption in multi-service environments. Our dynamic Quality of Service (QoS) Guarantee model utilizes hierarchical analysis to prioritize traffic among multiple service data streams and employs a service scheduling algorithm based on a weighted fair queue to allocate link resources. For user convenience, we have also created an intuitive web orchestration platform called EasyOrchestrator, enabling users to encapsulate common VNFs and build services quickly. Our experimental evaluation has shown that EasyOrchestrator significantly reduces service construction time compared to the benchmark. At the same time, our QoS assurance mechanism effectively minimizes network congestion and ensures the successful operation of high-priority services.