PowerGuide: Accurate Wi-Fi power estimator for smartphones

Abstract

Wi-Fi is a popular wireless communication technology for smart devices such as smartphones, however, Wi-Fi related energy consumption in smartphones contributes to a significant portion of its energy expenditure. Hence it is important to carefully analyze and profile Wi-Fi energy expenditure in order to improve mobile applications' energy efficiency. Although hardware based power meters provide very accurate power measurement result, it is infeasible to expect mobile application developers to rely on power meters. As alternative solutions, software based power estimation tools are popular. Most of the existing power estimation solutions to date do not provide accurate estimation result, as we disclose in this paper by analyzing the popular PowerTutor. Therefore, we propose a new Wi-Fi power model by taking into account important IEEE 802.11 communication patterns as well as Wi-Fi hardware settings in a way that increases the accuracy of power estimation. We design and implement the proposed power model as a smartphone application and deploy it into a real device for validation. The evaluation results show that our solution can achieve an estimation accuracy up to 86% compared to hardware power meters, and is much more accurate than PowerTutor.