eDoctor: automatically diagnosing abnormal battery drain issues on smartphones

Xiao Ma, Peng Huang, Xinxin Jin, Pei Wang, Soyeon Park, Dongcai Shen, Yuanyuan Zhou, Lawrence K. Saul, Geoffrey M. Voelker

2013 · 99 citations · 47 references

Concepts

Abstract

The past few years have witnessed an evolutionary change in the smartphone ecosystem. Smartphones have gone from closed platforms containing only pre-installed applications to open platforms hosting a variety of thirdparty applications. Unfortunately, this change has also led to a rapid increase in Abnormal Battery Drain (ABD) problems that can be caused by software defects or misconfiguration. Such issues can drain a fully-charged battery within a couple of hours, and can potentially affect a significant number of users. This paper presents eDoctor, a practical tool that helps regular users troubleshoot abnormal battery drain issues on smartphones. eDoctor leverages the concept of execution phases to capture an app’s time-varying behavior, which can then be used to identify an abnormal app. Based on the result of a diagnosis, eDoctor suggests the most appropriate repair solution to users. To evaluate eDoctor’s effectiveness, we conducted both in-lab experiments and a controlled user study with 31 participants and 17 realworld ABD issues together with 4 injected issues in 19 apps. The experimental results show that eDoctor can successfully diagnose 47 out of the 50 use cases while imposing no more than 1.5 % of power overhead. 1

References

47