FSM-based Wi-Fi power estimation method for smart devices

Abstract

With the increased popularity of mobile data applications, Wi-Fi power consumption on smartphones is now a significant portion of mobile energy expenditure. In their efforts to develop more energy efficient applications, the applications developers use energy estimation tools as a benchmark. Although hardware based power meter has high estimation accuracy, it is cumbersome to operate as it relies on physically attaching wires to the battery, and moreover the price of hardware based power meter is expensive. Therefore software based power estimation tools such as PowerTutor are popular. In our prior research using PowerTutor as power meter, we discovered that PowerTutor has large Wi-Fi power estimation error (over 1000%) on post 2012 phones. In this work, we propose a new FSM-based Wi-Fi power model based on IEEE 802.11 communication patterns and Wi-Fi hardware configuration with significantly increased power estimation accuracy. We designed and implemented our power model as an estimation tool called PowerGuide. Our experiments with PowerGuide in field operations showed that PowerGuide can achieve an average estimation accuracy of 86% compared to hardware power meters even with moderate polling period.