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Characterization of User’s Behavior Variations for Design of Replayable Mobile Workloads

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Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST,volume 162)

Abstract

Mobile systems leverage heterogeneous cores to deliver a desired user experience. However, how these cores cooperate in executing interactive mobile applications in the hands of a real user is unclear, preventing more realistic studies on mobile platforms. In this paper, we study how 33 users run applications on modern smartphones over a period of a month. We analyze the usage of CPUs, GPUs and associated memory operations in real user interactions, and develop microbenchmarks on an automated methodology which describes realistic and replayable test runs that statistically mimic user variations. Based on the generated test runs, we further empirically characterize memory bandwidth and power consumption of CPUs and GPUs to show the impact of user variations in the system, and identify user variation-aware optimization opportunities in actual mobile application uses.

Keywords

  • Mobile device
  • User variation
  • Heterogeneous cores
  • GPU usage

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Notes

  1. 1.

    The study participants include undergraduate and graduate students. Even though we collected the data from the on-campus students, we could find a wide range of variations in mobile usages.

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Acknowledgments

This work was supported in part by TerraSwarm, one of six centers of STARnet, a Semiconductor Research Corporation program sponsored by MARCO and DARPA, National Science Foundation (NSF) award 1344153 and Qualcomm.

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Correspondence to Yeseong Kim .

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Patil, S., Kim, Y., Korgaonkar, K., Awwal, I., Rosing, T.S. (2015). Characterization of User’s Behavior Variations for Design of Replayable Mobile Workloads. In: Sigg, S., Nurmi, P., Salim, F. (eds) Mobile Computing, Applications, and Services. MobiCASE 2015. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 162. Springer, Cham. https://doi.org/10.1007/978-3-319-29003-4_4

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  • DOI: https://doi.org/10.1007/978-3-319-29003-4_4

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-29002-7

  • Online ISBN: 978-3-319-29003-4

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