超5G边缘结构上的确定性服务功能链接
Deterministic Service Function Chaining over Beyond 5G Edge Fabric
摘要：
随着对延迟敏感的服务和应用的需求不断增加，最近提出了确定性网络（DetNet）概念，以研究5G边缘网络中具有有限延迟要求的服务的确定性延迟保证。网络功能虚拟化（NFV）技术使互联网服务提供商（ISP）能够灵活地放置虚拟网络功能（VNF），从而实现性能和成本效益。然后，通过以预定义的顺序引导业务通过一系列VNF实例来形成服务功能链（SFC）。此外，所需的网络资源和沿着SFC的VNF实例的放置应该被优化以满足确定性延迟要求。因此，确定一个最佳的SFC部署策略，以确保网络性能，同时提高网络收入，是非常重要的ISP。在本文中，我们共同研究了5G边缘网络中的资源分配和SFC放置，以确保确定性延迟。我们制定这个问题作为一个数学规划模型的目标最大化的整体网络利润的ISP。此外，提出了一种新的确定性SFC部署（Det-SFCD）算法，有效地嵌入SFC请求与确定性延迟保证。性能评估结果表明，与基准策略相比，该算法在SFC请求接受率、网络成本降低和网络资源利用率方面具有更好的性能。
英文摘要：
Along with the increasing demand for latencysensitive services and applications, Deterministic Network (DetNet) concept has been recently proposed to investigate deterministic latency assurance for services featured with bounded latency requirements in 5G edge networks. The Network Function Virtualization (NFV) technology enables Internet Service Providers (ISPs) to flexibly place Virtual Network Functions (VNFs) achieving performance and cost benefits. Then, Service Function Chains (SFC) are formed by steering traffic through a series of VNF instances in a predefined order. Moreover, the required network resources and placement of VNF instances along SFC should be optimized to meet the deterministic latency requirements. Therefore, it is significant for ISPs to determine an optimal SFC deployment strategy to ensure network performance while improving the network revenue. In this paper, we jointly investigate the resource allocation and SFC placement in 5G edge networks for deterministic latency assurance. We formulate this problem as a mathematic programming model with the objective of maximizing the overall network profit for ISP. Furthermore, a novel Deterministic SFC deployment (Det-SFCD) algorithm is proposed to efficiently embed SFC requests with deterministic latency assurance. The performance evaluation results show that the proposed algorithm can provide better performance in terms of SFC request acceptance rate, network cost reduction, and network resource efficiency compared with benchmark strategy.
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。
