{"title":"速度指数:将用户感知的Web性能与Web QoE的工业标准联系起来","authors":"T. Hossfeld, Florian Metzger, D. Rossi","doi":"10.1109/QoMEX.2018.8463430","DOIUrl":null,"url":null,"abstract":"In 2012, Google introduced the Speed Index (SI) metric to quantify the speed of the Web page visual completeness for the actually displayed above-the-fold (ATF) portion of a Web page. In Web browsing a page might appear to the user to be already fully rendered, even though further content may still be retrieved, resulting in the Page Load Time (PLT). This happens due to the browser progressively rendering all objects, part of which can also be located below the browser window's current viewport. The SI metric (and variants) thereof have since established themselves as a de facto standard in Web page and browser testing. While SI is a step in the direction of including the user experience into Web metrics, the actual meaning of the metric and especially its relationship between Speed Index and Web QoE is however far from being clear. The contributions of this paper are thus to first develop an understanding of the SI based on a theoretical analysis and second, to analyze the interdependency between SI and MOS values from an existing public dataset. Specifically, our analysis is based on two well established models that map the user waiting time to a user ACR-rating of the QoE. The analysis show that ATF-based metrics are more appropriate than pure PLT as input to Web QoE models.","PeriodicalId":6618,"journal":{"name":"2018 Tenth International Conference on Quality of Multimedia Experience (QoMEX)","volume":"36 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"38","resultStr":"{\"title\":\"Speed Index: Relating the Industrial Standard for User Perceived Web Performance to web QoE\",\"authors\":\"T. Hossfeld, Florian Metzger, D. Rossi\",\"doi\":\"10.1109/QoMEX.2018.8463430\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In 2012, Google introduced the Speed Index (SI) metric to quantify the speed of the Web page visual completeness for the actually displayed above-the-fold (ATF) portion of a Web page. In Web browsing a page might appear to the user to be already fully rendered, even though further content may still be retrieved, resulting in the Page Load Time (PLT). This happens due to the browser progressively rendering all objects, part of which can also be located below the browser window's current viewport. The SI metric (and variants) thereof have since established themselves as a de facto standard in Web page and browser testing. While SI is a step in the direction of including the user experience into Web metrics, the actual meaning of the metric and especially its relationship between Speed Index and Web QoE is however far from being clear. The contributions of this paper are thus to first develop an understanding of the SI based on a theoretical analysis and second, to analyze the interdependency between SI and MOS values from an existing public dataset. Specifically, our analysis is based on two well established models that map the user waiting time to a user ACR-rating of the QoE. The analysis show that ATF-based metrics are more appropriate than pure PLT as input to Web QoE models.\",\"PeriodicalId\":6618,\"journal\":{\"name\":\"2018 Tenth International Conference on Quality of Multimedia Experience (QoMEX)\",\"volume\":\"36 1\",\"pages\":\"1-6\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"38\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 Tenth International Conference on Quality of Multimedia Experience (QoMEX)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/QoMEX.2018.8463430\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 Tenth International Conference on Quality of Multimedia Experience (QoMEX)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/QoMEX.2018.8463430","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 38
摘要
2012年,Google引入了速度指数(Speed Index, SI)指标,用于量化Web页面实际显示在页面上方(ATF)部分的Web页面视觉完整性的速度。在Web浏览中,一个页面对用户来说可能已经完全呈现,即使可能仍然检索到更多的内容,从而导致页面加载时间(page Load Time, PLT)。这是由于浏览器逐渐呈现所有对象,其中一部分也可以位于浏览器窗口当前视口的下方。SI度量(及其变体)已经成为Web页面和浏览器测试中的实际标准。虽然SI是将用户体验纳入Web指标的一个步骤,但是指标的实际含义,特别是速度指数和Web QoE之间的关系还远未明确。因此,本文的贡献在于首先在理论分析的基础上发展对SI的理解,其次,从现有的公共数据集中分析SI和MOS值之间的相互依赖性。具体来说,我们的分析是基于两个完善的模型,它们将用户等待时间映射到QoE的用户acr评级。分析表明,基于atf的度量比纯PLT更适合作为Web QoE模型的输入。
Speed Index: Relating the Industrial Standard for User Perceived Web Performance to web QoE
In 2012, Google introduced the Speed Index (SI) metric to quantify the speed of the Web page visual completeness for the actually displayed above-the-fold (ATF) portion of a Web page. In Web browsing a page might appear to the user to be already fully rendered, even though further content may still be retrieved, resulting in the Page Load Time (PLT). This happens due to the browser progressively rendering all objects, part of which can also be located below the browser window's current viewport. The SI metric (and variants) thereof have since established themselves as a de facto standard in Web page and browser testing. While SI is a step in the direction of including the user experience into Web metrics, the actual meaning of the metric and especially its relationship between Speed Index and Web QoE is however far from being clear. The contributions of this paper are thus to first develop an understanding of the SI based on a theoretical analysis and second, to analyze the interdependency between SI and MOS values from an existing public dataset. Specifically, our analysis is based on two well established models that map the user waiting time to a user ACR-rating of the QoE. The analysis show that ATF-based metrics are more appropriate than pure PLT as input to Web QoE models.