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Web Font Optimization for Mobile Internet Users : A performance study of resource prioritization approaches for optimizing custom fonts on the web

According to the HTTP Archive, 75% of websites are using web fonts. Multiple conditions have to be met before modern web browsers like Chrome, Firefox and Safari decide to download the web fonts needed on a page. As a result, web fonts are late discovered resources that can delay the First Meaningful Paint (FMP). Improving the FMP is relevant for the web industry, particularly for performance-conscious web developers. This paper gives insight into how the resource prioritization approaches HTTP/2 Preload and HTTP/2 Server Push can be used to optimize the delivery of web fonts for first-time visitors. Five font loading strategies that use HTTP/2 Server Push and/or Preload were implemented on replicas of the landing pages from five real-world websites. The font loading strategies were evaluated against each other, and against the non-optimized version of each landing page. All the evaluated font loading strategies in this degree project improved the time it took to deliver the first web font content to the user’s screen, resulting in a faster FMP. It was also discovered that HTTP/2 Server Push, on its own, is not a more performance efficient resource prioritization approach than HTTP/2 Preload when it comes to delivering web font content to the client. Further, HTTP/2 Server Push and HTTP/2 Preload appears to be more efficient when used together, in the context of optimizing the delivery of web font content. However, all conclusions in this paper are based on the results gathered from testing the font loading strategies in an emulated environment and are yet to be confirmed on actual mobile devices with real network conditions.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:lnu-85481
Date January 2019
CreatorsNygren, Maria
PublisherLinnéuniversitetet, Institutionen för datavetenskap och medieteknik (DM)
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess

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