Improving Web Browsing Experience with Personalized Edge Computing

2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS) Pub Date : 2019-10-01 DOI:10.1109/IUCC/DSCI/SmartCNS.2019.00149

Zhaoxin Wu, Yasushi Shinjo

{"title":"Improving Web Browsing Experience with Personalized Edge Computing","authors":"Zhaoxin Wu, Yasushi Shinjo","doi":"10.1109/IUCC/DSCI/SmartCNS.2019.00149","DOIUrl":null,"url":null,"abstract":"In recent years, webpages are becoming complex rapidly and their loading times are also becoming longer. This paper tackles this problem with personalized edge computing. In typical edge computing, an edge server collaborates with cloud web servers. In personalized edge computing, on the other hand, an edge server called an Edge Server in the Middle (ESM) collaborates with users' mobile devices. Based on personalized edge computing, this paper focuses on two techniques: edge aided caching and edge aided reprioritizing. Edge aided caching reduces the page loading time on mobile devices because an ESM automatically keeps the cached components up to date. Edge aided reprioritizing forces a web browser to show visual components earlier and reduces the white screen time. The ESM also uses HTTP/2 instead of HTTP/1.1. This reduces the number of interactions between a mobile device and the ESM, and makes it possible to use advanced features such as server push and priority. Edge aided caching has been implemented in a PC for the web browser Google Chrome for Android. An experimental result shows that edge aided caching reduced the page loading time of a popular webpage by 59% in a crowded network condition. Another experimental result shows that edge aided reprioritizing reduced the white screen time of a webpage with many photo images by 21%.","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IUCC/DSCI/SmartCNS.2019.00149","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 1

Abstract

In recent years, webpages are becoming complex rapidly and their loading times are also becoming longer. This paper tackles this problem with personalized edge computing. In typical edge computing, an edge server collaborates with cloud web servers. In personalized edge computing, on the other hand, an edge server called an Edge Server in the Middle (ESM) collaborates with users' mobile devices. Based on personalized edge computing, this paper focuses on two techniques: edge aided caching and edge aided reprioritizing. Edge aided caching reduces the page loading time on mobile devices because an ESM automatically keeps the cached components up to date. Edge aided reprioritizing forces a web browser to show visual components earlier and reduces the white screen time. The ESM also uses HTTP/2 instead of HTTP/1.1. This reduces the number of interactions between a mobile device and the ESM, and makes it possible to use advanced features such as server push and priority. Edge aided caching has been implemented in a PC for the web browser Google Chrome for Android. An experimental result shows that edge aided caching reduced the page loading time of a popular webpage by 59% in a crowded network condition. Another experimental result shows that edge aided reprioritizing reduced the white screen time of a webpage with many photo images by 21%.

查看原文本刊更多论文

利用个性化边缘计算改善网页浏览体验

近年来，网页变得越来越复杂，加载时间也越来越长。本文利用个性化边缘计算解决了这一问题。在典型的边缘计算中，边缘服务器与云web服务器协同工作。另一方面，在个性化边缘计算中，称为中间边缘服务器(ESM)的边缘服务器与用户的移动设备协同工作。在个性化边缘计算的基础上，重点研究了边缘辅助缓存和边缘辅助重优先级两种技术。边缘辅助缓存减少了移动设备上的页面加载时间，因为ESM会自动使缓存的组件保持最新状态。Edge辅助的重新排序迫使web浏览器更早地显示可视化组件，并减少白屏时间。ESM也使用HTTP/2而不是HTTP/1.1。这减少了移动设备和ESM之间的交互次数，并使使用服务器推送和优先级等高级功能成为可能。Edge辅助缓存已经在PC上实现，用于Android的网络浏览器Google Chrome。实验结果表明，在拥挤的网络条件下，边缘辅助缓存使热门网页的页面加载时间缩短了59%。另一个实验结果表明，边缘辅助重新排序可以减少含有许多照片图像的网页的白屏时间21%。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)

自引率

0.00%

发文量