Betas: Deriving quantiles from MOS-QoS relations of IQX models for QoE management

T. Hossfeld, M. Fiedler, Jorgen Gustafsson
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引用次数: 6

Abstract

Most Quality of Experience (QoE) studies report only the mean opinion scores (MOS) and existing models typically map Quality of Service (QoS) parameters to the MOS. However, service providers may be interested in the share of users that are not at all satisfied, and their corresponding QoE levels. From the QoE management point of view, the circumstances leading to the QoE levels perceived by a certain percentage of users, e.g. the 10% most annoyed users, are of utmost importance. Proper metrics are the 10%-quantiles of QoE values. Knowledge of those quantiles helps service providers to estimate the need for countermeasures in order to prevent annoyed users from churning on one hand, and to avoid overprovisioning on the other hand. The contribution of this paper is the derivation of quantiles from existing MOS-QoS relations. This allows to reuse existing subjective MOS results and MOS models without rerunning the experiments. We consider exemplary the IQX model (describing the MOS-QoS relation) for the derivation of the quantile-QoS relation. A practical guideline for the computation of the quantiles is provided.
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beta:从IQX模型的MOS-QoS关系中导出分位数,用于QoE管理
大多数体验质量(QoE)研究仅报告平均意见分数(MOS),现有模型通常将服务质量(QoS)参数映射到MOS。然而,服务提供者可能对完全不满意的用户份额及其相应的QoE水平感兴趣。从QoE管理的角度来看,导致一定比例用户感知到QoE水平的环境,例如10%最烦人的用户,是最重要的。适当的指标是QoE值的10%分位数。了解这些分位数可以帮助服务提供商估计对策的需要,一方面防止烦恼的用户流失,另一方面避免过度供应。本文的贡献在于从现有的MOS-QoS关系中推导出分位数。这允许重用现有的主观MOS结果和MOS模型,而无需重新运行实验。我们考虑用于派生分位数- qos关系的IQX模型(描述MOS-QoS关系)作为示例。给出了计算分位数的实用指南。
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