Battery-Aware Transformations in Mobile Applications

被引：6

作者：

Cito, Jurgen ^{[1
]}

Rubin, Julia ^{[2
]}

Stanley-Marbell, Phillip ^{[2
]}

Rinard, Martin ^{[2
]}

机构：

[1] Univ Zurich, Zurich, Switzerland

[2] MIT, 77 Massachusetts Ave, Cambridge, MA 02139 USA

来源：

2016 31ST IEEE/ACM INTERNATIONAL CONFERENCE ON AUTOMATED SOFTWARE ENGINEERING (ASE) | 2016年

关键词：

Energy efficiency; battery lifetime; mobile advertisements; program analysis;

D O I：

10.1145/2970276.2970324

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

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.

引用

页码：702 / 707

页数：6