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Wireless Sensor Networks for Big Data Systems.

Beom-Su Kim1, Ki-Il Kim2, Babar Shah3

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Summary
This summary is machine-generated.

Wireless sensor networks (WSNs) generate big data but face reliability challenges. This survey explores WSNs for big data systems, detailing applications, challenges, and future research directions.

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Area of Science:

  • Computer Science
  • Data Science
  • Network Engineering

Background:

  • Wireless Sensor Networks (WSNs) are significant sources of big data due to numerous sensor nodes.
  • WSNs present unique challenges in data reliability and communication efficiency.
  • Dense deployment of sensor nodes leads to redundant and uninteresting data.

Purpose of the Study:

  • To provide a comprehensive survey of research on integrating WSNs into big data systems.
  • To identify and explain potential applications and technical challenges.
  • To highlight open issues and suggest future research avenues.

Main Methods:

  • Literature review of state-of-the-art research.
  • Analysis of WSN integration in big data contexts.
  • Categorization of challenges and applications.

Main Results:

  • Identified key limitations of WSNs for big data, including reliability and redundancy.
  • Cataloged various applications of WSNs in big data environments.
  • Detailed technical challenges related to WSN infrastructure and data processing.

Conclusions:

  • WSNs offer rich big data potential but require solutions for inherent limitations.
  • Further research is needed to optimize WSNs for robust big data applications.
  • Addressing open issues will pave the way for more effective WSN-based big data systems.