eDoctor: automatically diagnosing abnormal battery drain issues on smartphones

  • Authors:

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

  • Affiliations:

  • Univ. of California at San Diego and Univ. of Illinois at Urbana-Champaign;Univ. of California at San Diego;Univ. of California at San Diego;Peking Univ., China;Univ. of California at San Diego;Univ. of California at San Diego;Univ. of California at San Diego;Univ. of California at San Diego;Univ. of California at San Diego

  • Venue:
  • nsdi'13 Proceedings of the 10th USENIX conference on Networked Systems Design and Implementation
  • Year:
  • 2013

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Abstract

The past few years have witnessed an evolutionary change in the smartphone ecosystem. Smartphones have gone from closed platforms containing only preinstalled 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 real-world 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.