Rights statement: 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It has been recommended by the Editor-in-Chief of the IEEE Computer Architecture Letters that t his article will not be published in its final form.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
Accepted author manuscript, 1.03 MB, PDF document
Available under license: CC BY-NC: Creative Commons Attribution-NonCommercial 4.0 International License
Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - Adaptive Web Browsing on Mobile Heterogeneous Multi-cores
AU - Ren, Jie
AU - Wang, Xiaoming
AU - Fang, Jianbin
AU - Feng, Yansong
AU - Wang, Zheng
N1 - 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It has been recommended by the Editor-in-Chief of the IEEE Computer Architecture Letters that t his article will not be published in its final form.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
PY - 2018/9/24
Y1 - 2018/9/24
N2 - 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.
AB - 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.
U2 - 10.1109/LCA.2018.2869814
DO - 10.1109/LCA.2018.2869814
M3 - Journal article
JO - IEEE Computer Architecture Letters
JF - IEEE Computer Architecture Letters
ER -