Battery-aware transformations in mobile applications

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.