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Use of mobile network analytics for application performance design

机译：使用移动网络分析进行应用程序性能设计

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摘要

With the 5G technology, data traffic is going to grow by a factor of 1000, while the number of connected devices is likely going to be two orders of magnitude higher. With smartphones being cornerstone in our daily lives, understanding mobile network performance is critical for providing a superior user experience and, consequently, determining the success of an application. This paper presents a solution that uses the radio parameters measured by a mobile terminal to determine the best Application Protocol (APPP) for a service, so as it could adapt to the varying network conditions. From the training of an inference system with actual Mean Opinion Score (MOS) data, it will be possible to discern which radio Key Performance Indicators (KPIs) are best suited to characterize the state of the network and make the best possible decision. Results show how the decision system based on only three radio KPI is able to determine the user application experience with a success of up to 83%. Thanks to the use of this approach, application developers may fill the gap of knowledge between network KPIs and user experience.
机译：借助5G技术，数据流量将增长1000倍，而连接设备的数量可能会高出两个数量级。由于智能手机已成为我们日常生活的基石，因此了解移动网络性能对于提供出色的用户体验并因此决定应用程序的成功至关重要。本文提出了一种解决方案，该解决方案使用移动终端测量的无线电参数来确定服务的最佳应用协议（APPP），从而使其能够适应变化的网络条件。通过使用实际的平均意见评分（MOS）数据训练推理系统，可以分辨出最适合表征网络状态的无线电关键性能指标（KPI），并做出最佳决策。结果表明，仅基于三个无线电KPI的决策系统如何能够确定用户应用体验，成功率高达83％。由于使用了这种方法，应用程序开发人员可以填补网络KPI和用户体验之间的知识空白。

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