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Predictive Prefetching Based on User Interaction for Web Applications
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DOI：10.1109/LCOMM.2020.3038255.png)
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Abstract
En 中文
Web prefetching is a key technology to hide network latencies from users. Conventional prefetching methods, however, misconstrue the purpose of user's browsing behaviors and resulting experience due to their dependence on statistical characteristics or metadata of individual Web applications. In this letter, we propose a predictive prefetching scheme, WebPrefetcher, which utilizes interaction events to decipher user's genuine intention and context. Our intensive performance analysis results obtained with a real Web browser demonstrate that WebPrefetcher improves user-perceived quality of experience noticeably, outperforming competitive models.
Keywords:
Prefetching
Browsers
Engines
Quality of experience
Uniform resource locators
Predictive models
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Web prefetching
user interaction
quality of experience
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