arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2201.05453cs.NI
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下一代网络中基于ML/AI的移动业务使用预测

Towards ML/AI-based Prediction of Mobile Service Usage in Next-Generation Networks

T. Taleb, A. Laghrissi, D. E. Bensalem

摘要:

机器学习技术在下一代网络中的应用越来越受到研究界的关注。这是为了提供自适应学习和决策方法,以满足不同垂直行业的要求,并在复杂的移动场景中保证适当的性能要求。从这个角度来看,移动服务使用的特性是一个基本的步骤。在这种情况下,本文重点介绍了“网络切片规划器”(NSP)在其第二版中提供的新特性和功能[12]。提出了一种结合监督学习和无监督学习技术的方法来分析大量移动用户的服务消费行为。我们利用NSP v2提供的数据进行分析。此外,我们提供了一个评估的准确性的预测和性能的基础MEC基础设施。

英文摘要:

The adoption of machine learning techniques in next-generation networks has increasingly attracted the attention of the research community. This is to provide adaptive learning and decision-making approaches to meet the requirements of different verticals, and to guarantee the appropriate performance requirements in complex mobility scenarios. In this perspective, the characterization of mobile service usage represents a funda-mental step. In this vein, this paper highlights the new features and capabilities offered by the "Network Slice Planner"(NSP) in its second version [12]. It also proposes a method combining both supervised and unsupervised learning techniques to analyze the behavior of a mass of mobile users in terms of service consumption. We exploit the data provided by the NSP v2 to conduct our analysis. Furthermore, we provide an evaluation of both the accuracy of the predictor and the performance of the underlying MEC infrastructure.

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。

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