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Mobile Big Data pp 1–11Cite as

Mobile Big Data

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Part of the book series: Wireless Networks ((WN))

Abstract

The smart phone evolution in the past decade has accelerated the proliferation of mobile Internet and spurred a new wave of mobile applications on smart phones. In particular, GPS is becoming part of the default configuration of any smart mobile devices, rendering location information readily available. Even in the lack of exact location information when GPS is not enabled, the coarse location can still be inferred from the network-level data. The location information alone can already enable a great variety of applications to provide personalized services (context-aware recommendation, next location prediction based traffic time estimation, etc.) and to assist public service planning (e.g., traffic flow analysis, transportation management, city zone recognition, etc.). As smart phones are equipped with a variety of sensors, personal behaviors can be further learned and monitored. In addition, mobile operators can also collect a huge amount of data to monitor the technical and transactional aspects of their networks. It has been recently recognized that such data, known as mobile big data, could well be an under-exploited gold mine for almost all societal sectors.

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Author information

Authors and Affiliations

  1. State Key Laboratory of Advanced Optical Communication Systems and Networks, School of Electronics Engineering and Computing Science, Peking University, Beijing, China

    Xiang Cheng

  2. Department of Electrical & Computing Engineering, Colorado State University, Fort Collins, CO, USA

    Luoyang Fang & Liuqing Yang

  3. Department of Electrical and Computer Engineering, University of California - Davis, Davis, CA, USA

    Shuguang Cui

Authors
  1. Xiang Cheng
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  2. Luoyang Fang
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  3. Liuqing Yang
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  4. Shuguang Cui
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Cheng, X., Fang, L., Yang, L., Cui, S. (2018). Mobile Big Data. In: Mobile Big Data. Wireless Networks. Springer, Cham. https://doi.org/10.1007/978-3-319-96116-3_1

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  • DOI: https://doi.org/10.1007/978-3-319-96116-3_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-96115-6

  • Online ISBN: 978-3-319-96116-3

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