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Energy-Efficient Communication Using Data Aggregation and Data Compression Techniques in Wireless Sensor Networks: A Survey

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Advances in Communication, Signal Processing, VLSI, and Embedded Systems

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 614))

Abstract

Wireless Sensor Network (WSN) has been emerging as the most promising technology of future communication. WSNs face numerous research challenges, and one such challenge is the limited batteries in sensors. Thus, the data communication in WSNs has to be energy efficient. As nodes are densely deployed, data sensed by them are more likely to be correlated. This can be considered as an advantage to compress and combine the data from different nodes in WSNs. Ample number of researchers have worked in this area, and a good number of data compression and data aggregation algorithms were proposed in literature. In this paper, an attempt has been made in summarizing and comparing different compression and data aggregation algorithms proposed for WSN applications.

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Author information

Authors and Affiliations

  1. Department of DECS, VTU Centre for PG Studies, Mysuru, India

    S. Pushpalatha

  2. Department of ECE, N.M.A.M. Institute of Technology, Nitte, India

    K. S. Shivaprakasha

Authors
  1. S. Pushpalatha
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  2. K. S. Shivaprakasha
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Corresponding author

Correspondence to S. Pushpalatha .

Editor information

Editors and Affiliations

  1. Singapore University of Technology and Design, Singapore, Singapore

    Shubhakar Kalya

  2. National Institute of Technology Karnataka, Mangalore, Karnataka, India

    Muralidhar Kulkarni

  3. Department of Electronics and Communication Engineering, N.M.A.M. Institute of Technology, Nitte, Karkala, Karnataka, India

    K.S. Shivaprakasha

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Pushpalatha, S., Shivaprakasha, K.S. (2020). Energy-Efficient Communication Using Data Aggregation and Data Compression Techniques in Wireless Sensor Networks: A Survey. In: Kalya, S., Kulkarni, M., Shivaprakasha, K. (eds) Advances in Communication, Signal Processing, VLSI, and Embedded Systems. Lecture Notes in Electrical Engineering, vol 614. Springer, Singapore. https://doi.org/10.1007/978-981-15-0626-0_14

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  • DOI: https://doi.org/10.1007/978-981-15-0626-0_14

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-0625-3

  • Online ISBN: 978-981-15-0626-0

  • eBook Packages: EngineeringEngineering (R0)

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