research-article

How much energy can we save from prefetching ads?: energy drain analysis of top 100 apps

Authors:

Xiaomeng Chen,

Abhilash Jindal,

Y. Charlie HuAuthors Info & Claims

HotPower '13: Proceedings of the Workshop on Power-Aware Computing and Systems

Article No.: 3, Pages 1 - 5

https://doi.org/10.1145/2525526.2525848

Published: 03 November 2013 Publication History

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Abstract

Recently, there has been a surge of interests on developing techniques and architectures for prefetching ads to potentially reduce the smartphone energy drain by 3G/4G radios from fetching ads. Despite the development of prefetching techniques, it remains unclear (1) how much smartphone energy do ads consume in popular apps in dominant app markets, and (2) out of which, what portion can we realistically save from prefetching?

We present a measurement study of the energy drain of top 100 free apps in Google Play, totaling more than 2.2 B downloads, to re-examine the above two motivational questions for ads energy research. We found the upper bound energy savings from prefetching ads is low: out of the top 100 apps, only 57 apps display ads, which incur on average 3.2% total energy on ads 3G tails. We further show the already-low upper bound ads energy saving is hard to achieve by ads prefetching as different apps exhibit very different ads behavior.

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Cited By

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Hort MKechagia MSarro FHarman M(2022)A Survey of Performance Optimization for Mobile ApplicationsIEEE Transactions on Software Engineering10.1109/TSE.2021.307119348:8(2879-2904)Online publication date: 1-Aug-2022
https://doi.org/10.1109/TSE.2021.3071193
Ginny Kumar CNaik K(2020)Smartphone processor architecture, operations, and functions: current state-of-the-art and future outlook: energy performance trade-offThe Journal of Supercomputing10.1007/s11227-020-03312-z77:2(1377-1454)Online publication date: 16-May-2020
https://doi.org/10.1007/s11227-020-03312-z
Li YWang YLan T(2019)Mobile Ad Prefetching and Energy Optimization via Tail Energy AccountingIEEE Transactions on Mobile Computing10.1109/TMC.2018.287359618:9(2117-2128)Online publication date: 1-Sep-2019
https://doi.org/10.1109/TMC.2018.2873596
Show More Cited By

How much energy can we save from prefetching ads?: energy drain analysis of top 100 apps
1. General and reference
  1. Cross-computing tools and techniques

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HotPower '13: Proceedings of the Workshop on Power-Aware Computing and Systems

November 2013

66 pages

ISBN:9781450324588

DOI:10.1145/2525526

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 03 November 2013

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SIGOPS

SOSP '13: ACM SIGOPS 24th Symposium on Operating Systems Principles

November 3 - 6, 2013

Pennsylvania, Farmington

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HotPower '13 Paper Acceptance Rate 13 of 38 submissions, 34%;

Overall Acceptance Rate 20 of 50 submissions, 40%

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Hort MKechagia MSarro FHarman M(2022)A Survey of Performance Optimization for Mobile ApplicationsIEEE Transactions on Software Engineering10.1109/TSE.2021.307119348:8(2879-2904)Online publication date: 1-Aug-2022
https://doi.org/10.1109/TSE.2021.3071193
Ginny Kumar CNaik K(2020)Smartphone processor architecture, operations, and functions: current state-of-the-art and future outlook: energy performance trade-offThe Journal of Supercomputing10.1007/s11227-020-03312-z77:2(1377-1454)Online publication date: 16-May-2020
https://doi.org/10.1007/s11227-020-03312-z
Li YWang YLan T(2019)Mobile Ad Prefetching and Energy Optimization via Tail Energy AccountingIEEE Transactions on Mobile Computing10.1109/TMC.2018.287359618:9(2117-2128)Online publication date: 1-Sep-2019
https://doi.org/10.1109/TMC.2018.2873596
Montenegro JPinto MFuentes L(2018)What Do Software Developers Need to Know to Build Secure Energy-Efficient Android Applications?IEEE Access10.1109/ACCESS.2017.27791316(1428-1450)Online publication date: 2018
https://doi.org/10.1109/ACCESS.2017.2779131
Cito JRubin JStanley-Marbell PRinard MLo DApel SKhurshid S(2016)Battery-aware transformations in mobile applicationsProceedings of the 31st IEEE/ACM International Conference on Automated Software Engineering10.1145/2970276.2970324(702-707)Online publication date: 25-Aug-2016
https://dl.acm.org/doi/10.1145/2970276.2970324
Pujol EHohlfeld OFeldmann ACho KFukuda KPai VSpring N(2015)Annoyed UsersProceedings of the 2015 Internet Measurement Conference10.1145/2815675.2815705(93-106)Online publication date: 28-Oct-2015
https://dl.acm.org/doi/10.1145/2815675.2815705
Hussein APayer MHosking AVick C(2015)Impact of GC design on power and performance for AndroidProceedings of the 8th ACM International Systems and Storage Conference10.1145/2757667.2757674(1-12)Online publication date: 26-May-2015
https://dl.acm.org/doi/10.1145/2757667.2757674
Nath SBorriello GPau GGruteser MHong J(2015)MAdScopeProceedings of the 13th Annual International Conference on Mobile Systems, Applications, and Services10.1145/2742647.2742653(59-73)Online publication date: 18-May-2015
https://dl.acm.org/doi/10.1145/2742647.2742653
Metri GShi WBrockmeyer MManweiler JChoudhury R(2015)Energy-Efficiency Comparison of Mobile Platforms and ApplicationsProceedings of the 16th International Workshop on Mobile Computing Systems and Applications10.1145/2699343.2699358(39-44)Online publication date: 12-Feb-2015
https://dl.acm.org/doi/10.1145/2699343.2699358
Mouawi RElhajj IChehab AKayssi A(2015)Comparison of in-app ads traffic in different ad networks2015 IEEE 11th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)10.1109/WiMOB.2015.7348014(581-587)Online publication date: Oct-2015
https://doi.org/10.1109/WiMOB.2015.7348014

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Prefetching mobile ads: can advertising systems afford it?

Can offloading save energy for popular apps?

Energy-efficient hardware data prefetching

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