Predictive Prefetching Based on User Interaction for Web Applications

Minwoo Joo, Yeonoh An, Heejun Roh, Wonjun Lee

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
JournalIEEE Communications Letters
DOIs
Publication statusAccepted/In press - 2020

Keywords

  • Browsers
  • Engines
  • Loading
  • Predictive models
  • Prefetching
  • Quality of experience
  • quality of experience
  • Uniform resource locators
  • user interaction
  • Web prefetching

ASJC Scopus subject areas

  • Modelling and Simulation
  • Computer Science Applications
  • Electrical and Electronic Engineering

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