{"title":"基于层次分析法的QoE因子选择新方法","authors":"Y. B. Youssef, Mériem Afif, S. Tabbane","doi":"10.1109/AICCSA.2016.7945727","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":448329,"journal":{"name":"2016 IEEE/ACS 13th International Conference of Computer Systems and Applications (AICCSA)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Novel AHP-based QoE factors' selection approach\",\"authors\":\"Y. B. Youssef, Mériem Afif, S. Tabbane\",\"doi\":\"10.1109/AICCSA.2016.7945727\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":448329,\"journal\":{\"name\":\"2016 IEEE/ACS 13th International Conference of Computer Systems and Applications (AICCSA)\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE/ACS 13th International Conference of Computer Systems and Applications (AICCSA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AICCSA.2016.7945727\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE/ACS 13th International Conference of Computer Systems and Applications (AICCSA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AICCSA.2016.7945727","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
摘要
随着互联网上多媒体业务的发展,体验质量(Quality of Experience, QoE)评估已成为一个重要的课题。虽然目前的QoE预测模型关注以技术为中心的服务质量(QoS)参数作为影响用户感知质量的主要关键,但它们没有充分解决以下问题:“基于QoS,是否能够理解整体的QoE?”质量质量评价模型存在两个局限性:(1)缺乏在评价模型中引入的因子;(2)检验各因子对质量质量影响的研究有限。从更全面的角度看待影响质量质量的因素,促使研究者对质量质量的多维层面进行深入研究。为了应对这一挑战,并考虑到理解QoE及其影响因素的重要性,我们在本文中的贡献是给出一个解决方案,以绕过上述限制。本文提出了一种基于多准则决策理论衍生的层次分析法(AHP)的选择因子设计方法。结果表明,基于我们的模型,我们可以检索到影响因素的排序。本文的相关目标是给出一个结构化的过程来考察影响质量质量的因素。未来的QoE评估模型可以从应用我们提出的模型中受益,以便构建尽可能真实的QoE模型。
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.