Smartphone Energizer: Extending Smartphone´s battery life with smart offloading

This paper presents “Smartphone Energizer”, a novel technique for context-aware computation offloading for smartphones. Previous techniques to the offloading problem were based on a narrow set of contextual information, which made the amount of energy saving varies unexpectedly based on the context in which the application is running. Smartphone Energizer uses the benefit of supervised learning with a rich set of contextual information such as application, device, network, and user characteristics to optimize both the energy consumption and execution time of Smartphone´s applications in a variety of contextual situations. In our evaluation, we show that Smartphone Energizer predicts both energy consumption and execution time in different contexts with error less than 9%, which in turn helped in taking the right offloading decision and saving energy by 40% to 56% and execution time by 43% to 58%.