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Big Data Analytics Platforms for Real-Time Applications in IoT

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Big Data Analytics

Abstract

Big data platforms have predominantly focused on the volume aspects of large-scale data management. The growing pervasiveness of Internet of Things (IoT) applications, along with their associated ability to collect data from physical and virtual sensors continuously, highlights the importance of managing the velocity dimension of big data too. In this chapter, we motivate the analytics requirements of IoT applications using several practical use cases, characterize the trade-offs between processing latency and data volume capacity of contemporary big data platforms, and discuss the critical role that Distributed Stream Processing and Complex Event Processing systems play in addressing the analytics needs of IoT applications.

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Author information

Authors and Affiliations

  1. Department of Computational and Data Sciences, Indian Institute of Science, Bangalore, India

    Yogesh Simmhan

  2. WSO2, Colombo, Sri Lanka

    Srinath Perera

Authors
  1. Yogesh Simmhan
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  2. Srinath Perera
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Corresponding author

Correspondence to Yogesh Simmhan .

Editor information

Editors and Affiliations

  1. Indian Institute of Public Health , Hyderabad, India

    Saumyadipta Pyne

  2. CRRao AIMSCS, University of Hyderabad Campus CRRao AIMSCS, Hyderabad, India

    B.L.S. Prakasa Rao

  3. CRRao AIMSCS, University of Hyderabad Campus CRRao AIMSCS, Hyderabad, India

    S.B. Rao

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Simmhan, Y., Perera, S. (2016). Big Data Analytics Platforms for Real-Time Applications in IoT. In: Pyne, S., Rao, B., Rao, S. (eds) Big Data Analytics. Springer, New Delhi. https://doi.org/10.1007/978-81-322-3628-3_7

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