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Issue No. 06 - June (2017 vol. 16)
ISSN: 1536-1233
pp: 1773-1785
Yi Gao , College of Computer Science, Zhejiang University, Zhejiang, China
Wei Dong , College of Computer Science, Zhejiang University, Zhejiang, China
Haocheng Huang , College of Computer Science, Zhejiang University, Zhejiang, China
Jiajun Bu , College of Computer Science, Zhejiang University, Zhejiang, China
Chun Chen , College of Computer Science, Zhejiang University, Zhejiang, China
Mingyuan Xia , School of Computer Science, McGill University, Canada
Xue Liu , School of Computer Science, McGill University, Canada
ABSTRACT
The past decade has witnessed a tremendous growth in the variety and complexity of mobile applications (apps). Although considerable amount of efforts have been spent to improve app performance, smartphones nowadays still face many performance challenges. We discover that the resource contention of multiple running apps, caused by resource bottleneck(s), is a key factor that affects the smartphone performance. In this paper, we present APB, an A utomatic tool that detects Performance issues caused by resource B ottleneck(s) on commodity Android smartphones. APB employs an innovative bottleneck-hypersurface model to quantify performance issues given a specific system state. Then, based on the model, APB identifies a list of apps that contribute most to the resource contention, which can well inform the end user to take action such as killing background apps to resolve the performance issue. We implement APB on commodity Android platforms and widely evaluate its effectiveness with real user studies. Results show that APB outperforms three baseline approaches and helps users to improve smartphone performance by 10 to 67 percent, with less than 1 percent runtime overhead.
INDEX TERMS
Smart phones, Resource management, Computer bugs, Androids, Humanoid robots, Measurement, Mobile computing
CITATION

Y. Gao et al., "Whom to Blame? Automatic Diagnosis of Performance Bottlenecks on Smartphones," in IEEE Transactions on Mobile Computing, vol. 16, no. 6, pp. 1773-1785, 2017.
doi:10.1109/TMC.2016.2604258
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