Managing big data experiments on smartphones

Abstract

The explosive number of smartphones with ever growing sensing and computing capabilities have brought a paradigm shift to many traditional domains of the computing field. Re-programming smartphones and instrumenting them for application testing and data gathering at scale is currently a tedious and time-consuming process that poses significant logistical challenges. Next generation smartphone applications are expected to be much larger-scale and complex, demanding that these undergo evaluation and testing under different real-world datasets, devices and conditions. In this paper, we present an architecture for managing such large-scale data management experiments on real smartphones. We particularly present the building blocks of our architecture that encompassed smartphone sensor data collected by the crowd and organized in our big data repository. The given datasets can then be replayed on our testbed comprising of real and simulated smartphones accessible to developers through a web-based interface. We present the applicability of our architecture through a case study that involves the evaluation of individual components that are part of a complex indoor positioning system for smartphones, coined Anyplace, which we have developed over the years. The given study shows how our architecture allows us to derive novel insights into the performance of our algorithms and applications, by simplifying the management of large-scale data on smartphones.

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Notes

  1. 1.

    Available at http://smartlab.cs.ucy.ac.cy/

  2. 2.

    Anyplace, http://anyplace.cs.ucy.ac.cy/

  3. 3.

    Kanaka, https://github.com/kanaka/websockify/

  4. 4.

    Free Software Foundation Europe, http://goo.gl/fZZQe

  5. 5.

    Available under “Code” tab at http://dmsl.cs.ucy.ac.cy

  6. 6.

    DMSL VCenter @ UCY. http://goo.gl/dZfTE5

  7. 7.

    HAProxy. http://haproxy.1wt.eu/

  8. 8.

    Couchbase. http://www.couchbase.com/

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Acknowledgments

We would like to thank the anonymous reviewers for their valuable comments and suggestions. This work was supported in part by the last author’s Startup Grant, funded by the University of Cyprus, COST Action IC903 (MOVE) “Knowledge Discovery for Moving Objects” EU’s FP7 (MODAP) “Mobility, Data Mining, and Privacy” projects, as well as an industrial grant by MTN Cyprus.

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Correspondence to Demetrios Zeinalipour-Yazti.

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Larkou, G., Mintzis, M., Andreou, P.G. et al. Managing big data experiments on smartphones. Distrib Parallel Databases 34, 33–64 (2016). https://doi.org/10.1007/s10619-014-7158-6

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Keywords

  • Experimental testbed
  • Big data
  • Sensor mockups
  • Smartphones