Energy-Aware Web Browsing on Smartphones

Zhao, Bo; Hu, Wenjie; Zheng, Qiang; Cao, Guohong

doi:10.1109/tpds.2014.2312931

Cited by 51 publications

(27 citation statements)

References 23 publications

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“…There have been studies on managing power consumption by considering the wireless link [27,44,46]. The works [27] and [44] analyze the 3G protocol and suggest the reorganization of data transmission phases.…”

Section: Related Workmentioning

confidence: 99%

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Phase-Aware Web Browser Power Management on HMP Platforms

Peters

Park

Clifford

et al. 2018

Proceedings of the 2018 International Conference on Supercomputing

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Over the last years, web browsing has been steadily shifting from desktop computers to mobile devices like smartphones and tablets. However, mobile browsers available today have mainly focused on performance rather than power consumption, although the battery life of a mobile device is one of the most important usability metrics. This is because many of these browsers have originated in the desktop domain and have been ported to the mobile domain. Such browsers have multiple power hungry components such as the rendering engine, and the JavaScript engine, and generate high workload without considering the capabilities and the power consumption characteristics of the underlying hardware platform. Also, the lack of coordination between a browser application and the power manager in the operating system (such as Android) results in poor power savings. In this paper, we propose a power manager that takes into account the internal state of a browser -that we refer to as a phase -and show with Google's Chrome running on Android that up to 57.4% more energy can be saved over Android's default power managers. We implemented and evaluated our technique on a heterogeneous multi-processing (HMP) ARM big.LITTLE platform such as the ones found in most modern smartphones.

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Section: Related Workmentioning

confidence: 99%

“…The works [27] and [44] analyze the 3G protocol and suggest the reorganization of data transmission phases. Combining multiple fragmented transmissions into larger chunks gives more room for the wireless link to enter low power states and save power during web page loading.…”

Section: Related Workmentioning

confidence: 99%

Phase-Aware Web Browser Power Management on HMP Platforms

Peters

Park

Clifford

et al. 2018

Proceedings of the 2018 International Conference on Supercomputing

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“…Tang Lung Cheung et al [13] proposed a WiFi radio power optimization strategy which focused on the energy consumption of interface states, but had not taken the signal strength into consideration which also has great impact on user experience. And Bo Zhao et al [14] proposed an energy-aware approach for web browsing in 3G based smartphones by reconstructing the computation sequence for opening webpage and building the DOM tree.…”

Section: Related Work and Conclusionmentioning

confidence: 99%

Energy-Aware Download Method in LTE Based Smartphone

Ren

Gao

Wang

et al. 2017

IEICE Trans. Inf. & Syst.

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SUMMARYMobile traffic is experiencing tremendous growth, and this growing wave is no doubt increasing the use of radio component of mobile devices, resulting in shorter battery lifetime. In this paper, we present an Energy-Aware Download Method (EDM) based on the Markov Decision Process (MDP) to optimize the data download energy for mobile applications. Unlike the previous download schemes in literature that focus on the energy efficiency by simply delaying the download requests, which often leads to a poor user experience, our MDP model learns off-line from a set of training download workloads for different user patterns. The model is then integrated into the mobile application to deal the download request at runtime, taking into account the current battery level, LTE reference signal receiving power (RSRP), reference signal signal to noise radio (RSSNR) and task size as input of the decision process, and maximizes the reward which refers to the expected battery life and user experience. We evaluate how the EDM can be used in the context of a real file downloading application over the LTE network. We obtain, on average, 20.3%, 15% and 45% improvement respectively for energy consumption, latency, and performance of energy-delay trade off, when compared to the Android default download policy (Minimum Delay).

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“…The first has no any third party application 1 In this research, we used Nexus 5 as a mobile device for experiments and ODROID Smart Power for power measurement. "1,000"" "2,000"" "3,000"" "4,000"" "5,000"" Execu2on(Time((s)(…”

Section: Problem Of Background Services Using Wireless Network Imentioning

confidence: 99%

“…Wireless networks such as celluar, and WiFi consume more energy compared with the Ethernet. Thus, Zhao et al [1] try to exploit detailed wireless network technologies such as RRC (radio resource control) state machine to reduce the energy consumption. Moreover, unlike the studies in [2], [3] of the causes unable to enter the sleep mode because of the wake-lock and energy bugs, Park et al [4] present a scheme, which excludes non-critical alarms for the problems of wake-ups from the sleep state.…”

Section: Introductionmentioning

confidence: 99%

Energy-efficient batch scheduling for background network services in mobile devices

Kim

2016

2016 IEEE International Conference on Consumer Electronics (ICCE)

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Background services using wireless networks in mobile devices can receive and send data periodically without user interaction, so that users can get instantly recent information. However, indiscreet uses of the background services increase the energy consumption because of the frequent state machine changes of wireless network interfaces and low utilization of the idle state of the mobile devices. We propose a method to reduce the energy consumption using a batch sync scheduler, which controls the trigger time of background services. According to our experiments, it reduces the energy consumption by 8.4%.

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Energy-Aware Web Browsing on Smartphones

Cited by 51 publications

References 23 publications

Phase-Aware Web Browser Power Management on HMP Platforms

Phase-Aware Web Browser Power Management on HMP Platforms

Energy-Aware Download Method in LTE Based Smartphone

Energy-efficient batch scheduling for background network services in mobile devices

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