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Data Compression Technique for Wireless Sensor Networks

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Convergence and Hybrid Information Technology (ICHIT 2012)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7425))

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Abstract

Energy conservation is a critical issue in Wireless Sensor Networks since sensor nodes are powered by battery. As radio communications is the main source of energy consumption, reducing transmission overhead would be extended the sensor node lifetime. In this paper, we propose a data compressing technique using temporal correlation of sensing data, data transformation from one dimension to two dimension, and data separation: upper 8bit and lower 8bit data. From the simulation, the proposed algorithm has a well-directed technique and can be available to data rate control.

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Author information

Authors and Affiliations

  1. Dept. of Information Communications Engineering, Chungnam National University, Yuseong-gu, Deajeon, Korea

    Joonki Min, Jookyoung Kim & Youngmi Kwon

Authors
  1. Joonki Min
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  2. Jookyoung Kim
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  3. Youngmi Kwon
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Editor information

Editors and Affiliations

  1. Dept of Computer Engineering, Hannam University, Korea

    Geuk Lee

  2. Computer Science and Information System, University of Limerick, Limerick, Ireland

    Daniel Howard

  3. Department of Information and Communication, Dong Seoul University, 423 Bokjeong-Dong, Sujeong-Gu, Seongnam, Gyunggi, Korea

    Jeong Jin Kang

  4. Institute of Mathematics, University of Warsaw, ul. Banacha 2, 02-097, Warsaw, Poland

    Dominik Ślęzak

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© 2012 Springer-Verlag Berlin Heidelberg

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Min, J., Kim, J., Kwon, Y. (2012). Data Compression Technique for Wireless Sensor Networks. In: Lee, G., Howard, D., Kang, J.J., Ślęzak, D. (eds) Convergence and Hybrid Information Technology. ICHIT 2012. Lecture Notes in Computer Science, vol 7425. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32645-5_2

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  • DOI: https://doi.org/10.1007/978-3-642-32645-5_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32644-8

  • Online ISBN: 978-3-642-32645-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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