A simple data compression algorithm for wireless sensor networks

Jonathan Gana Kolo; Li Minn Ang; S. Anandan Shanmugam; David Wee Gin Lim; Kah Phooi Seng

doi:10.1007/978-3-642-32922-7_34

A simple data compression algorithm for wireless sensor networks

Jonathan Gana Kolo^*
, Li Minn Ang
, S. Anandan Shanmugam
, David Wee Gin Lim
, Kah Phooi Seng

^*Corresponding author for this work

Materials and Manufacturing Engineering
Edith Cowan University
Sunway University

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

13 Citations (Scopus)

Abstract

The energy consumption of each wireless sensor node is one of critical issues that require careful management in order to maximize the lifetime of the sensor network since the node is battery powered. The main energy consumer in each node is the communication module that requires energy to transmit and receive data over the air. Data compression is one of possible techniques that can reduce the amount of data exchanged between wireless sensor nodes. In this paper, we proposed a simple lossless data compression algorithm that uses multiple Huffman coding tables to compress WSNs data adaptively. We demonstrate the merits of our proposed algorithm in comparison with recently proposed LEC algorithm using various real-world sensor datasets.

Original language	English
Title of host publication	Soft Computing Models in Industrial and Environmental Applications - 7th International Conference, SOCO'12
Publisher	Springer Verlag
Pages	327-336
Number of pages	10
ISBN (Print)	9783642329210
DOIs	https://doi.org/10.1007/978-3-642-32922-7_34
Publication status	Published - 2013
Externally published	Yes
Event	7th International Conference on Soft Computing Models in Industrial and Environmental Applications, SOCO'12 - Ostrava, Czech Republic Duration: 5 Sept 2012 → 7 Sept 2012

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	188 AISC
ISSN (Print)	2194-5357

Conference

Conference	7th International Conference on Soft Computing Models in Industrial and Environmental Applications, SOCO'12
Country/Territory	Czech Republic
City	Ostrava
Period	5/09/12 → 7/09/12

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Adaptive Entropy Encoder
Data Compression
Energy Efficiency
Huffman Coding
Signal Processing
Wireless Sensor Networks

Access to Document

10.1007/978-3-642-32922-7_34

Cite this

Kolo, J. G., Ang, L. M., Shanmugam, S. A., Lim, D. W. G., & Seng, K. P. (2013). A simple data compression algorithm for wireless sensor networks. In Soft Computing Models in Industrial and Environmental Applications - 7th International Conference, SOCO'12 (pp. 327-336). (Advances in Intelligent Systems and Computing; Vol. 188 AISC). Springer Verlag. https://doi.org/10.1007/978-3-642-32922-7_34

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title = "A simple data compression algorithm for wireless sensor networks",

abstract = "The energy consumption of each wireless sensor node is one of critical issues that require careful management in order to maximize the lifetime of the sensor network since the node is battery powered. The main energy consumer in each node is the communication module that requires energy to transmit and receive data over the air. Data compression is one of possible techniques that can reduce the amount of data exchanged between wireless sensor nodes. In this paper, we proposed a simple lossless data compression algorithm that uses multiple Huffman coding tables to compress WSNs data adaptively. We demonstrate the merits of our proposed algorithm in comparison with recently proposed LEC algorithm using various real-world sensor datasets.",

keywords = "Adaptive Entropy Encoder, Data Compression, Energy Efficiency, Huffman Coding, Signal Processing, Wireless Sensor Networks",

author = "Kolo, \{Jonathan Gana\} and Ang, \{Li Minn\} and Shanmugam, \{S. Anandan\} and Lim, \{David Wee Gin\} and Seng, \{Kah Phooi\}",

year = "2013",

doi = "10.1007/978-3-642-32922-7\_34",

language = "English",

isbn = "9783642329210",

series = "Advances in Intelligent Systems and Computing",

publisher = "Springer Verlag",

pages = "327--336",

booktitle = "Soft Computing Models in Industrial and Environmental Applications - 7th International Conference, SOCO'12",

note = "7th International Conference on Soft Computing Models in Industrial and Environmental Applications, SOCO'12 ; Conference date: 05-09-2012 Through 07-09-2012",

}

Kolo, JG, Ang, LM, Shanmugam, SA, Lim, DWG & Seng, KP 2013, A simple data compression algorithm for wireless sensor networks. in Soft Computing Models in Industrial and Environmental Applications - 7th International Conference, SOCO'12. Advances in Intelligent Systems and Computing, vol. 188 AISC, Springer Verlag, pp. 327-336, 7th International Conference on Soft Computing Models in Industrial and Environmental Applications, SOCO'12, Ostrava, Czech Republic, 5/09/12. https://doi.org/10.1007/978-3-642-32922-7_34

A simple data compression algorithm for wireless sensor networks. / Kolo, Jonathan Gana; Ang, Li Minn; Shanmugam, S. Anandan et al.
Soft Computing Models in Industrial and Environmental Applications - 7th International Conference, SOCO'12. Springer Verlag, 2013. p. 327-336 (Advances in Intelligent Systems and Computing; Vol. 188 AISC).

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

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KW - Adaptive Entropy Encoder

KW - Data Compression

KW - Energy Efficiency

KW - Huffman Coding

KW - Signal Processing

KW - Wireless Sensor Networks

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BT - Soft Computing Models in Industrial and Environmental Applications - 7th International Conference, SOCO'12

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ER -

A simple data compression algorithm for wireless sensor networks

Abstract

Publication series

Conference

UN SDGs

Keywords

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