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Novel AHP-based QoE factors' selection approach

机译:基于AHP的新型QoE因子选择方法

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Due to the accelerating uptake of multimedia services over Internet, Quality of Experience (QoE) assessment has become a topic of prime importance. While current QoE prediction models focus on technology-centered Quality of Service (QoS) parameters as the main influencing keys on user's perception quality, they do not sufficiently address the following question: “Based upon QoS, is it competent to understand the overall QoE?” Two limitations on QoE models have been noticed: (1) lack of factors introducing in assessment models, and (2) studies that examine the impact of each factors on QoE are limited. The need to take a more holistic view of influencing QoE factors has steered researchers towards an in-depth study on the multidimensional aspect of QoE. In order to tackle this challenge and giving the growing importance of understanding QoE and the factors influencing it, our contribution in this paper is to give a solution to get around limits mentioned above. This paper proposes a proper design of selection factor based on the Analytic Hierarchy Process (AHP) derived from a Multi-Criteria Decision Making (MCDM) theory. The result shows that due to our model, we can retrieve a ranking of the influential factors. The relevant goal of this paper is to give a structured process that examines influencing factors on QoE. Future QoE assessment models can benefit from applying our proposed model in order to build a QoE model as realistic as possible.
机译:由于Internet上多媒体服务的加速使用,体验质量(QoE)评估已成为最重要的主题。尽管当前的QoE预测模型将技术中心的服务质量(QoS)参数作为影响用户感知质量的主要关键因素,但它们并不能充分解决以下问题:“基于QoS,是否有能力理解整体QoE? ”已注意到QoE模型的两个局限性:(1)评估模型中缺乏引入因素的因素;(2)检查每种因素对QoE的影响的研究是有限的。需要对影响QoE的因素有更全面的了解,这促使研究人员对QoE的多维方面进行了深入研究。为了应对这一挑战,并使理解QoE及其影响因素的重要性越来越高,我们在本文中的贡献在于提供一种解决上述问题的解决方案。本文提出了一种基于多准则决策(MCDM)理论的层次分析法(AHP),对选择因子进行适当的设计。结果表明,由于我们的模型,我们可以检索影响因素的排名。本文的相关目标是给出一个结构化的过程,以检查影响QoE的因素。未来的QoE评估模型可以从应用我们提出的模型中受益,从而构建尽可能切合实际的QoE模型。

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