The performance of distributed and data-centric applications often critically depends on the interconnecting network. Applications are hence modeled as virtual networks, also accounting for resource demands on links. At the heart of provisioning such virtual networks lies the NP-hard Virtual Network Embedding Problem (VNEP): how to jointly map the virtual nodes and links onto a physical substrate network at minimum cost while obeying capacities. This paper studies the VNEP in the light of parameterized complexity. We focus on tree topology substrates, a case often encountered in practice and for which the VNEP remains NP-hard. We provide the first fixed-parameter algorithm for the VNEP with running time $O(3^r (s+r^2))$ for requests and substrates of $r$ and $s$ nodes, respectively. In a computational study our algorithm yields running time improvements in excess of 200x compared to state-of-the-art integer programming approaches. This makes it comparable in speed to the well-established ViNE heuristic while providing optimal solutions. We complement our algorithmic study with hardness results for the VNEP and related problems.
翻译:分布式和以数据为中心的应用程序的性能往往主要取决于相互连接的网络。应用程序因此以虚拟网络为模型,同时也考虑到对链接的资源需求。提供这种虚拟网络的核心是NP-硬虚拟网络嵌入问题(VNEP ):如何在服从能力下以最低成本联合绘制虚拟节点和链接到物理基底网络(VNEP ) : 如何在服从能力下以最低成本绘制虚拟节点和链接到物理基底网络。本文根据参数化复杂度对VNEP 进行了研究。 我们侧重于树木地形基质,这是在实践中经常遇到的一个案例,VNEP仍然坚固。 我们为VNEP提供了第一个固定参数算法, 运行时间为O( 3°r (s+R% 2) 美元), 运行时间分别为 $ 和 $ $s@s nodes 。 在一项计算研究中, 我们的算法比状态整数式编程法方法提高了200x, 使时间的改进幅度超过200x。这在速度上可以比完善的VNE Heurist,同时提供最佳的解决方案。我们用精确结果来补充我们的算学结果。