Mobile Edge Computing (MEC) is a promising network architecture that pushes network control and mobile computing to the network edge. Recent studies propose to deploy MEC applications in the Network Function Virtualization (NFV) environment. The mobile network service in NFV is deployed as a Service Function Chaining (SFC). In the dynamic and resource-limited mobile network, SFC placement aiming at optimizing resource utilization is a challenging problem. In this article, we solve the SFC placement problem in the MEC-NFV environment. We formulate the SFC placement problem as a weighted graph matching problem, including two sub-problems: a graph matching problem and an SFC mapping problem. To efficiently solve the graph matching problem, we propose a Linear Programming–(LP) based approach to calculate the similarity between VNFs and physical nodes. Based on the similarity, we design a Hungarian-based algorithm to solve the SFC mapping problem. Evaluation results show that our proposed LP-based solutions outperform the heuristic algorithms in terms of execution time and resource utilization.

中文翻译：

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移动边缘计算中一种高效的服务功能链放置算法

移动边缘计算（MEC）是一种很有前途的网络架构，它将网络控制和移动计算推向网络边缘。最近的研究建议在网络功能虚拟化 (NFV) 环境中部署 MEC 应用程序。NFV 中的移动网络服务部署为服务功能链 (SFC)。在动态和资源有限的移动网络中，旨在优化资源利用的SFC放置是一个具有挑战性的问题。在本文中，我们解决了 MEC-NFV 环境中的 SFC 放置问题。我们将 SFC 放置问题表述为加权图匹配问题，包括两个子问题：图匹配问题和 SFC 映射问题。为了有效地解决图匹配问题，我们提出了一种基于线性规划（LP）的方法来计算 VNF 和物理节点之间的相似度。基于相似性，我们设计了一种基于匈牙利的算法来解决 SFC 映射问题。评估结果表明，我们提出的基于 LP 的解决方案在执行时间和资源利用率方面优于启发式算法。