放松是好的：具有延迟约束的虚拟网络的快速利润近似
It's Good to Relax: Fast Profit Approximation for Virtual Networks with Latency Constraints
摘要：
针对具有时延约束的离线虚拟网络嵌入问题，提出了一种新的近似算法。给出了一组虚拟网络，其中节点上有计算需求，边缘上有带宽需求和延迟界限。VNEP的任务是在共享物理基础设施上可行地嵌入虚拟网络的子集，例如，一个数据中心，同时最大化所获得的利润。在现有的作品相比，我们的近似算法AFlex允许（轻微）违反的延迟约束，以大大降低运行时间。为了获得这一结果，我们使用的限制最短路径问题（RSP）的减少，并利用Goel等人的经典结果。我们补充了我们的正式分析与广泛的模拟研究，证明我们的方法经验的计算优势。值得注意的是，我们的结果推广到任何其他加性边缘度量除了延迟，包括丢失概率。
英文摘要：
This paper proposes a new approximation algorithm for the offline Virtual Network Embedding Problem (VNEP) with latency constraints. Given is a set of virtual networks with computational demands on nodes and bandwidth demands together with latency bounds on the edges. The VNEP's task is to feasibly embed a subset of virtual networks on a shared physical infrastructure, e.g., a data center, while maximizing the attained profit. In contrast to existing works, our approximation algorithm AFlex allows for (slight) violations of the latency constraints in order to greatly lower the runtime. To obtain this result, we use a reduction to the Restricted Shortest Path Problem (RSP) and leverage a classic result by Goel et al. We complement our formal analysis with an extensive simulation study demonstrating the computational benefits of our approach empirically. Notably, our results generalize to any other additive edge metric besides latency, including loss probability.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
