{"title":"A QoE Prediction Model Combining Network Parameters and Video Quality","authors":"Jinfan Zhao, Shufeng Li, Feng Hu","doi":"10.1109/CoST57098.2022.00016","DOIUrl":null,"url":null,"abstract":"The advent of the 5G era and the theater performing arts market woes caused by Corona Virus Disease 2019 (COVID- 2019) epidemic have accelerated the emergence and growth of the cloud performing arts business. To improve the quality of service for cloud performing arts and live performances, it is critical to develop a predictive model that accurately and timely reflects the Quality of Experience (QoE). In this paper, we first filter three of the seven recognized application layer Quality of Service (QoS) parameters that represent the input network quality in this QoE prediction model. Then one of the four different video quality evaluation methods is selected as the most effective method to represent the video quality. The purpose of combining network quality and video quality is to build a more accurate and effective QoE prediction model.","PeriodicalId":135595,"journal":{"name":"2022 International Conference on Culture-Oriented Science and Technology (CoST)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Culture-Oriented Science and Technology (CoST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CoST57098.2022.00016","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The advent of the 5G era and the theater performing arts market woes caused by Corona Virus Disease 2019 (COVID- 2019) epidemic have accelerated the emergence and growth of the cloud performing arts business. To improve the quality of service for cloud performing arts and live performances, it is critical to develop a predictive model that accurately and timely reflects the Quality of Experience (QoE). In this paper, we first filter three of the seven recognized application layer Quality of Service (QoS) parameters that represent the input network quality in this QoE prediction model. Then one of the four different video quality evaluation methods is selected as the most effective method to represent the video quality. The purpose of combining network quality and video quality is to build a more accurate and effective QoE prediction model.