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Battery-Aware Transformations in Mobile Applications


Cito, Jürgen; Rubin, Julia; Stanley-Marbell, Phillip; Rinard, Martin (2016). Battery-Aware Transformations in Mobile Applications. In: 31st IEEE/ACM International Conference on Automated Software Engineering (ASE 2016), Singapore, 3 September 2016 - 7 September 2016.

Abstract

We present an adaptive binary transformation system for reducing the energy impact of advertisements and analytics in mobile applications. Our approach accommodates both the needs of mobile app developers to obtain income from advertisements and the desire of mobile device users for longer battery life. Our technique automatically identifies recurrent advertisement and analytics requests and throttles these requests based on a mobile device's battery status. Of the Android applications we analyzed, 75% have at least one connection that exhibits such recurrent requests. Our automated detection scheme classifies these requests with 100% precision and 80.5% recall. Applying the proposed battery-aware transformations to a representative mobile application reduces the power consumption of the mobile device
by 5.8%, without the negative effect of completely removing advertisements.

Abstract

We present an adaptive binary transformation system for reducing the energy impact of advertisements and analytics in mobile applications. Our approach accommodates both the needs of mobile app developers to obtain income from advertisements and the desire of mobile device users for longer battery life. Our technique automatically identifies recurrent advertisement and analytics requests and throttles these requests based on a mobile device's battery status. Of the Android applications we analyzed, 75% have at least one connection that exhibits such recurrent requests. Our automated detection scheme classifies these requests with 100% precision and 80.5% recall. Applying the proposed battery-aware transformations to a representative mobile application reduces the power consumption of the mobile device
by 5.8%, without the negative effect of completely removing advertisements.

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Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Language:English
Event End Date:7 September 2016
Deposited On:05 Aug 2016 09:00
Last Modified:08 Dec 2017 20:07
Publisher:ACM
Publisher DOI:https://doi.org/10.1145/2970276.2970324
Related URLs:http://www.ase2016.org/ (Organisation)
Other Identification Number:merlin-id:13541

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