Network slicing is a powerful tool to harness the full potential of 5G systems. It allows verticals to own and exploit independent logical networks on top of the same physical infrastructure. Motivated by the emergence of the big data paradigm, this article focuses on the enablers of big-databased intelligent network slicing. The article starts by revisiting the architecture of this technology that consists of data collection, storage, processing, and analytics before it highlights their relationship with network slicing concepts and the underlying trade-offs. It then proposes a complete framework for implementing big-data-driven dynamic slicing resource provisioning while respecting SLAs. This includes the development of low-complexity slices' traffic predictors, resource allocation models, and SLA enforcement via constrained deep learning. The article finally identifies the key challenges and open research directions in this emerging area.

中文翻译：

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大数据助力5G智能网络切片管理


网络切片是充分发挥 5G 系统潜力的强大工具。它允许垂直行业拥有并利用同一物理基础设施之上的独立逻辑网络。受大数据范式出现的推动，本文重点关注基于大数据的智能网络切片的推动者。本文首先重新审视该技术的架构，其中包括数据收集、存储、处理和分析，然后重点介绍它们与网络切片概念和底层权衡的关系。然后，它提出了一个完整的框架，用于在尊重 SLA 的同时实施大数据驱动的动态切片资源配置。这包括开发低复杂性切片的流量预测器、资源分配模型以及通过约束深度学习执行 SLA。文章最后确定了这一新兴领域的关键挑战和开放研究方向。