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Automatic Best Wireless Network Selection Based on Key Performance Indicators

机译:基于关键性能指标的自动最佳无线网络选择

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摘要

Introducing cognitive mechanisms at the application layer may lead to the possibility of an automatic selection of the wireless network that can guarantee best perceived experience by the final user. This chapter investigates this approach based on the concept of Quality of Experience (QoE), by introducing the use of application layer parameters, namely Key Performance Indicators (KPIs). KPIs are defined for different traffic types based on experimental data. A model for an ap- plication layer cognitive engine is presented, whose goal is to identify and select, based on KPIs, the best wireless network among available ones. An experimenta- tion for the VoIP case, that foresees the use of the One-way end-to-end delay (OED) and the Mean Opinion Score (MOS) as KPIs is presented. This first implementation of the cognitive engine selects the network that, in that specific instant, offers the best QoE based on real captured data. To our knowledge, this is the first example of a cognitive engine that achieves best QoE in a context of heterogeneous wireless networks.
机译:在应用层的认知机制引入可能导致自动选择可以保证最终用户最佳感知体验的无线网络的可能性。本章通过引入应用层参数的使用,即关键绩效指标(KPI)来研究基于经验质量(QoE)的概念来调查这种方法。基于实验数据,KPI定义为不同的交通类型。提出了一种用于聚合层认知引擎的模型,其目标是基于KPI识别和选择可用的KPI中最佳无线网络。对VoIP案例的实验,例如,使用单向端到端延迟(OED)和均值的均值(MOS)作为KPI的使用。第一次实现认知引擎选择该网络,在该特定瞬间,基于真实捕获的数据提供最佳QoE。为了我们的知识,这是在异构无线网络的背景下实现最佳QoE的认知引擎的第一例。

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