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Energy-Efficient Localization via Personal Mobility Profiling

  • Conference paper

Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST,volume 35)

Abstract

Location based services are on the rise, many of which assume GPS based localization. Unfortunately, GPS incurs an unacceptable energy cost that can reduce the phone’s battery life to less than ten hours. Alternate localization technology, based on WiFi or GSM, improve battery life at the expense of localization accuracy. This paper quantifies this important tradeoff that underlies a wide range of emerging applications. To address this tradeoff, we show that humans can be profiled based on their mobility patterns, and such profiles can be effective for location prediction. Prediction reduces the energy consumption due to continuous localization. Driven by measurements from Nokia N95 phones, we develop an energy-efficient localization framework called EnLoc. Evaluation on real user traces demonstrates the possibility of achieving good localization accuracy for a realistic energy budget.

Keywords

  • Mobile Phone
  • Energy Budget
  • Linear Prediction
  • Average Localization Error
  • Personal Mobility

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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  • DOI: 10.1007/978-3-642-12607-9_14
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© 2010 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering

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Constandache, I., Gaonkar, S., Sayler, M., Choudhury, R.R., Cox, L. (2010). Energy-Efficient Localization via Personal Mobility Profiling. In: Phan, T., Montanari, R., Zerfos, P. (eds) Mobile Computing, Applications, and Services. MobiCASE 2009. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 35. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12607-9_14

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  • DOI: https://doi.org/10.1007/978-3-642-12607-9_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-12606-2

  • Online ISBN: 978-3-642-12607-9

  • eBook Packages: Computer ScienceComputer Science (R0)