边缘计算中基于网站分类的优先级控制

N. Kamiyama, Yuusuke Nakano, K. Shiomoto, G. Hasegawa, M. Murata, H. Miyahara
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引用次数: 6

摘要

现代网站由许多丰富的对象组成,这些对象由位于不同位置的服务器和客户端动态生成。为了高效地交付动态对象,将对象动态生成并交付到位于边缘节点的边缘服务器上的客户端终端的边缘计算将是有效的。可以预见,边缘计算的有效性取决于对象部署的地理格局,而对象的地理分布趋势在不同的网站类别(如体育和新闻)中是不同的,因此对边缘计算的网站类别进行优先排序似乎是有效的。在本文中,我们首先提出了一个测量每个网站类别中对象部署的地理趋势的平台。然后,我们提出基于测量的对象部署模式来区分边缘计算中不同网站类别的缓存优先级。通过使用PlanetLab访问来自全球12个地点的约1,000个最受欢迎的网站的经验,我们阐明,通过仔细区分网站类别之间的缓存优先级,我们可以将web响应时间的减少率提高约20%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Priority control based on website categories in edge computing
Modern websites consist of many rich objects dynamically produced by servers and client terminals at diverse locations. To deliver dynamic objects efficiently, edge computing in which objects are dynamically generated and delivered to client terminals on edge servers located at edge nodes will be effective. It is anticipated that the effectiveness of edge computing depends on the geographical pattern of object deployment, and the tendency of geographical distribution of objects is different among website categories, e.g., Sports and News, so it seems effective to prioritize website categories for edge computing. In this paper, we first propose a platform for measuring the geographical tendency of object deployment in each website category. We then propose to differentiate the caching priority in edge computing among website categories based on the measured deployment pattern of objects. Through the experience of accessing about 1,000 of the most popular websites from 12 locations worldwide using PlanetLab, we clarify that we can improve the reduction ratio of web response time by about 20% by carefully differentiating caching priority among website categories.
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