Mobile edge computing offers a myriad of opportunities to innovate and introduce novel applications, thereby enhancing user experiences considerably. A critical issue extensively investigated in this domain is efficient deployment of Service Function Chains (SFCs) across the physical network, spanning from the edge to the cloud. This problem is known to be NP-hard. As a result of its practical importance, there is significant interest in the development of high-quality sub-optimal solutions. In this paper, we consider this problem and propose a novel near-optimal heuristic that is extremely efficient and scalable. We compare our solution to the state-of-the-art heuristic and to the theoretical optimum. In our large-scale evaluations, we use realistic topologies which were previously reported in the literature. We demonstrate that the execution time offered by our solution grows slowly as the number of Virtual Network Function (VNF) forwarding graph embedding requests grows, and it handles one million requests in slightly more than 20 seconds for 100 nodes and 150 edges physical topology.

翻译：移动边缘计算为创新和引入新型应用提供了众多机遇，从而显著提升用户体验。该领域中一个被广泛研究的关键问题是如何在跨越边缘到云的物理网络上高效部署服务功能链（SFCs）。该问题已知为NP-hard。由于其实际重要性，开发高质量的次优解备受关注。本文针对该问题，提出一种新颖的近最优启发式算法，具有极高的效率和可扩展性。我们将所提方案与现有最优启发式算法及理论最优解进行了对比。在大规模评估中，我们采用了文献中已报道的真实拓扑。实验表明，随着虚拟网络功能（VNF）转发图嵌入请求数量的增加，所提方案的执行时间增长缓慢；在包含100个节点和150条边的物理拓扑上，处理一百万个请求的时间略多于20秒。