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Analysis of Data Aggregation Techniques in WSN

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Book cover International Conference on Innovative Computing and Communications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1059))

Abstract

Wireless sensor networks (WSNs) produce a huge amount of application-specific data. These data need to be processed and transmitted to base station, which is a costly affair. Since WSN nodes are resource-constrained, efficient data processing and conserving energy are prime challenges. It has been observed that most of the data sensed by the sensors are redundant in nature. If data redundancy can be reduced, then it will lead to an increased lifetime of the network and reduced latency. In this paper, we surveyed different techniques for reducing redundancy in data, and in particular through aggregation. We have discussed data aggregation taxonomy, challenges and critically analysed aggregation techniques proposed in the last 10 years.

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Notes

  1. 1.

    Packet length.

  2. 2.

    Node which aggregates the incoming data [38].

  3. 3.

    The sensing area in which sensors are deployed.

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Author information

Authors and Affiliations

  1. GD Goenka University, Gurgaon, Haryana, 122103, India

    Nihar Ranjan Roy

  2. School of Information, Communication and Technology, Guru Gobind Singh Indraprastha University, New Delhi, 110078, India

    Nihar Ranjan Roy & Pravin Chandra

Authors
  1. Nihar Ranjan Roy
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  2. Pravin Chandra
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Corresponding author

Correspondence to Nihar Ranjan Roy .

Editor information

Editors and Affiliations

  1. Computer Science and Engineering, Maharaja Agrasen Institute of Technology, Delhi, India

    Ashish Khanna

  2. Computer Science and Engineering, Maharaja Agrasen Institute of Technology, Delhi, India

    Deepak Gupta

  3. Department of Information Technology, RCC Institute of Information Technology, Kolkata, West Bengal, India

    Siddhartha Bhattacharyya

  4. Department of Computer Science, VŠB - Technical University of Ostrava, Ostrava-Poruba, Czech Republic

    Vaclav Snasel

  5. Department of Computer Science, VŠB - Technical University of Ostrava, Ostrava-Poruba, Czech Republic

    Jan Platos

  6. Faculty of Computers and Information, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

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Roy, N.R., Chandra, P. (2020). Analysis of Data Aggregation Techniques in WSN. In: Khanna, A., Gupta, D., Bhattacharyya, S., Snasel, V., Platos, J., Hassanien, A. (eds) International Conference on Innovative Computing and Communications. Advances in Intelligent Systems and Computing, vol 1059. Springer, Singapore. https://doi.org/10.1007/978-981-15-0324-5_48

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