An Exploratory Data Analytics Platform for Factories of Future

E. Zeydan, Ömer Dedeoglu
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引用次数: 1

Abstract

Factories of Future (FoF) is an emerging vertical sector towards 5G network evolution. Fine-grained monitoring the network performance of FoF environment can help to extract insight on the quality-of-service (QoS) of a given industrial service provided by next generation cellular technologies. However, one of the main solutins that mobile network operators (MNOs) are investing today is on data evaluation tools that can be integrated withing their network infrastructure. In this paper using the open-source analytics tools, we analyze the industrial network traffic characteristics behaviour of an operational cellular network of a MNO. Our results finds out the relationship between various key performance indicators (KPIs) and extract insights on the performance and operational aspects of a factory environment using the cellular networks data with ElasticSearch stack's data analytics capabilities.
面向未来工厂的探索性数据分析平台
未来工厂(FoF)是面向5G网络演进的新兴垂直领域。对FoF环境的网络性能进行细粒度监控有助于了解由下一代蜂窝技术提供的给定工业服务的服务质量(QoS)。然而,移动网络运营商(mno)目前投资的主要解决方案之一是可以集成到其网络基础设施中的数据评估工具。在本文中,我们使用开源分析工具,分析了一个移动运营商的操作蜂窝网络的工业网络流量特征行为。我们的结果发现了各种关键绩效指标(kpi)之间的关系,并使用蜂窝网络数据和ElasticSearch堆栈的数据分析功能提取了工厂环境的性能和操作方面的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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