Simultaneous Node-Link Mapping for Virtual Network Embedding in 5G/6G Environments Using GAT-Augmented PPO

Read the full article See related articles

Listed in

This article is not in any list yet, why not save it to one of your lists.
Log in to save this article

Abstract

With the evolution of 5G and the emerging 6G networks, Virtual Network Embedding (VNE) plays a critical role in enabling network slicing, ultra-low latency, and dynamic, multi-tenant resource sharing over a common physical infrastructure. However, the VNE problem—mapping virtual nodes and links to substrate network resources—is NP-hard, and conventional approaches rely on a sequential strategy that first maps nodes and then connects links. This disjoint process often results in inefficient embeddings, high rejection rates, and suboptimal Quality of Service (QoS), especially under dynamic and high-demand 5G/6G scenarios. To overcome these challenges, we propose a novel GAT-PPO-based adaptive VNE framework with simultaneous joint node-link mapping. Unlike traditional methods, our approach integrates Graph Attention Networks (GAT) to model complex spatial and topological correlations, and Proximal Policy Optimization (PPO) for intelligent, policy-driven decision-making in dynamic environments. The key innovation lies in early-stage joint embedding, where link mapping is initiated immediately after placing a minimal subset of nodes (e.g., two or three), ensuring that feasibility and resource constraints are evaluated holistically from the outset. This simultaneous mapping mechanism is particularly well-suited for 5G/6G network slicing environments, where heterogeneous service requirements (e.g., eMBB, URLLC, and mMTC) demand flexible, efficient, and adaptive embedding strategies. Our framework dynamically adapts to network load variations and topological changes, thereby improving resource utilization, service isolation, latency control, and the acceptance ratio of virtual network requests. Experimental evaluations on realistic topologies demonstrate significant performance gains over state-of-the-art baselines in terms of embedding cost, long-term revenue, and scalability—highlighting the framework’s potential to support the high-performance demands of next-generation mobile networks.

Article activity feed