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INFOCOM2021顶会

Web-LEGO: Trading Content Strictness for Faster Webpages

Pengfei Wang, Matteo Varvello, Chunhe Ni, Ruiyun Yu, Aleksandar Kuzmanovic

2021年份
4被引次数

摘要

The current Internet content delivery model assumes strict mapping between a resource and its descriptor, e.g., a JPEG file and its URL. Content Distribution Networks (CDNs) extend it by replicating the same resources across multiple locations, and introducing multiple descriptors. The goal of this work is to build Web-LEGO, an opt-in service, to speedup webpages at client side. Our rationale is to replace the slow original content with fast similar or equal content. Further, we perform a reality check of this idea both in term of the prevalence of CDN-less websites, availability of similar content, and user perception of similar webpages via millions of scale automated tests and thousands of real users. Then, we devise Web-LEGO, and address natural concerns on content inconsistency and copyright infringements. The final evaluation shows that Web-LEGO brings significant improvements both in term of reduced Page Load Time (PLT) and user-perceived PLT. Specifically, CDN-less websites provide more room for speedup than CDN-hosted ones, i.e., 7x more in the median case. Besides, Web-LEGO achieves high visual accuracy (94.2%) and high scores from a paid survey: 92% of the feedback collected from 1,000 people confirm Web-LEGO's accuracy as well as positive interest in the service.

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