Adaptive Web Browsing on Mobile Heterogeneous Multi-cores

Ren, Jie and Wang, Xiaoming and Fang, Jianbin and Feng, Yansong and Wang, Zheng (2018) Adaptive Web Browsing on Mobile Heterogeneous Multi-cores. IEEE Computer Architecture Letters.

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Abstract

Web browsing is an important application domain, but it imposes a significant power burden on mobile devices. While the heterogeneous multi-core design offers the potential for energy-efficient computing, existing web browsers fail to exploit the hardware to optimize mobile web browsing. Our work aims to offer a better way to optimize web browsing on heterogeneous mobile devices. We achieve this by developing a machine learning based approach to predict the optimal processor setting for rendering the web content. The prediction is based on the web content, the network status and the optimization goal. We evaluate our approach by applying it to the Chromium browser and testing it on a representative big.LITTLE mobile platform. We apply our approach to the top 1,000 hottest websites across seven typical networking environments. Our approach achieves over 80% of the performance delivered by a perfect predictor. Our approach achieves over 30%, 50%, and 60% improvement respectively for load time, energy consumption and the energy delay product when compared to two state-of-the arts approaches.

Item Type:
Journal Article
Journal or Publication Title:
IEEE Computer Architecture Letters
Additional Information:
Notes: IEEE Xplore ® Notice to Reader: "Adaptive Web Browsing on Mobile Heterogeneous Multi-Cores" by J. Ren, X. Wang, J. Fang, Y. Feng, and Z. Wang published in IEEE Computer Architecture Letters Early Access Digital Object Identifier: 10.1109/LCA.2018.2869814 It has been recommended by the Editor-in-Chief of the IEEE Computer Architecture Letters that t his article will not be published in its final form. It should not be considered for citation purposes. We regret any inconvenience this may have caused. Daniel J. Sorin Editor-in-Chief IEEE Computer Architecture Letters
ID Code:
131047
Deposited By:
Deposited On:
04 Feb 2019 11:35
Refereed?:
Yes
Published?:
Published
Last Modified:
22 Nov 2022 06:17