Network slicing enables communication service providers to partition physical infrastructure into logically independent networks. Network slices must be provisioned to meet the service-level objectives (SLOs) of disparate offerings, such as enhanced mobile broadband, ultrareliable low-latency communications, and massive machine-type communications. Network orchestrators must customize service placement and scaling to achieve the SLO of each network slice. In this article, we discuss the challenges encountered by network orchestrators in allocating resources to disparate 5G network slices, and propose the use of artificial intelligence to make core placement and scaling decisions that meet the requirements of network slices deployed on shared infrastructure. We explore how artificial intelligence-driven scaling algorithms, coupled with functionality-aware placement, can enable providers to design closed-loop solutions to meet the disparate SLOs of future network slices.

中文翻译：

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5G核心中的AI驱动配置

网络切片使通信服务提供商可以将物理基础设施划分为逻辑上独立的网络。必须提供网络切片，以满足不同产品的服务级别目标（SLO），例如增强的移动宽带，超可靠的低延迟通信和大规模的机器类型通信。网络协调者必须自定义服务的放置和扩展，以实现每个网络切片的SLO。在本文中，我们讨论了网络协调者在分配资源以分散5G网络切片时遇到的挑战，并提出了使用人工智能来做出核心布局和扩展决策的方案，以满足共享基础架构上部署的网络切片的需求。我们探索了人工智能驱动的缩放算法，