演示:基于AI-Engine的B5G/6G网络智能管理

Haijun Zhang, Wanqing Guan, Dong Wang, Qize Song, A. Nallanathan
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引用次数: 0

摘要

在B5G和6G时代,不同垂直行业的业务需求日益复杂,智能化已成为无线网络的发展趋势。通过网络切片,多个服务可以共享基础设施的资源,并提供差异化的服务质量(QoS)保证。然而,网络实时状态的不确定性和动态性需要一种智能的管理方案。为了提高资源利用率,快速满足不同业务的资源需求,切片管理迫切需要人工智能(AI)算法。这个演示展示了一个封装了多种AI算法的AI引擎是如何为切片的生命周期管理做出贡献的。特别是,我们的解决方案考虑了人工智能引擎的分布式部署,并为各种用例提供了不同的机器学习(ML)模型。这也使AI-Engine能够支持边缘云中的网络功能和智能应用的数据分析。此外,该解决方案还允许调整AI-Engine的各个分布式组件的计算资源分配,以方便智能网络管理。
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Demo: AI-Engine Enabled Intelligent Management in B5G/6G Networks
In the B5G and 6G era, service demands of diverse vertical industries are becoming increasingly complex and intelligence has become the development trend of wireless networks. By means of network slicing, resources of the infrastructure can be shared by multiple services with differentiated quality of service (QoS) guarantees. However, the uncertainty and dynamics on real-time network status requires an intelligent management scheme. Artificial intelligence (AI) algorithms are urgently needed in slice management to improve resource utilization and quickly satisfy the resource requirements of different services. This demo shows how an AI-Engine that encapsulates multiple AI algorithms can contribute to the life-cycle management of slices. In particular, our solution considers distributed deployment of the AI-Engine and provides different machine learning (ML) models for various use cases. This also enables the AI-Engine to support data analysis of network functions and intelligent applications in the edge cloud. Furthermore, this solution allows to adjust computing resource allocation for each distributed component of the AI-Engine to facilitate the intelligent network management.
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