Predictive Prefetching Based on User Interaction for Web Applications

Minwoo Joo; Yeonoh An; Heejun Roh; Wonjun Lee

doi:10.1109/LCOMM.2020.3038255

Predictive Prefetching Based on User Interaction for Web Applications

Minwoo Joo
, Yeonoh An
, Heejun Roh
, Wonjun Lee

Research output: Contribution to journal › Article › peer-review

8 Citations (Scopus)

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 language	English
Article number	9260158
Pages (from-to)	821-824
Number of pages	4
Journal	IEEE Communications Letters
Volume	25
Issue number	3
DOIs	https://doi.org/10.1109/LCOMM.2020.3038255
Publication status	Published - 2021 Mar

Bibliographical note

Funding Information:
Manuscript received September 17, 2020; revised October 23, 2020; accepted November 11, 2020. Date of publication November 16, 2020; date of current version March 10, 2021. This research was partly supported by the NRF grant funded by the Korea government (MSIT) (No. 2019R1A2C2088812) and Next-Generation Information Computing Development Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (No. 2017M3C4A7083676). The associate editor coordinating the review of this letter and approving it for publication was W. Cerroni. (Corresponding author: Wonjun Lee.) The authors are with the Network and Security Research Laboratory, School of Cybersecurity, Korea University, Seoul 02841, South Korea (e-mail: [email protected]). Digital Object Identifier 10.1109/LCOMM.2020.3038255

Publisher Copyright:
© 1997-2012 IEEE.

Keywords

Web prefetching
quality of experience
user interaction

ASJC Scopus subject areas

Modelling and Simulation
Computer Science Applications
Electrical and Electronic Engineering

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10.1109/LCOMM.2020.3038255

Cite this

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title = "Predictive Prefetching Based on User Interaction for Web Applications",

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.",

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note = "Funding Information: Manuscript received September 17, 2020; revised October 23, 2020; accepted November 11, 2020. Date of publication November 16, 2020; date of current version March 10, 2021. This research was partly supported by the NRF grant funded by the Korea government (MSIT) (No. 2019R1A2C2088812) and Next-Generation Information Computing Development Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (No. 2017M3C4A7083676). The associate editor coordinating the review of this letter and approving it for publication was W. Cerroni. (Corresponding author: Wonjun Lee.) The authors are with the Network and Security Research Laboratory, School of Cybersecurity, Korea University, Seoul 02841, South Korea (e-mail: [email protected]). Digital Object Identifier 10.1109/LCOMM.2020.3038255 Publisher Copyright: {\textcopyright} 1997-2012 IEEE.",

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AU - Joo, Minwoo

AU - An, Yeonoh

AU - Roh, Heejun

AU - Lee, Wonjun

N1 - Funding Information: Manuscript received September 17, 2020; revised October 23, 2020; accepted November 11, 2020. Date of publication November 16, 2020; date of current version March 10, 2021. This research was partly supported by the NRF grant funded by the Korea government (MSIT) (No. 2019R1A2C2088812) and Next-Generation Information Computing Development Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (No. 2017M3C4A7083676). The associate editor coordinating the review of this letter and approving it for publication was W. Cerroni. (Corresponding author: Wonjun Lee.) The authors are with the Network and Security Research Laboratory, School of Cybersecurity, Korea University, Seoul 02841, South Korea (e-mail: [email protected]). Digital Object Identifier 10.1109/LCOMM.2020.3038255 Publisher Copyright: © 1997-2012 IEEE.

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Predictive Prefetching Based on User Interaction for Web Applications

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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