A simple data compression algorithm for wireless sensor networks

J G Kolo; Li-Minn Ang; S A Shanmugam; D W G Lim; K P Seng

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

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A simple data compression algorithm for wireless sensor networks

Conference paper

Peer reviewed

A simple data compression algorithm for wireless sensor networks

J G Kolo, Li-Minn Ang, S A Shanmugam, D W G Lim and K P Seng

Soft Computing Models in Industrial and Environmental Applications: 7th International Conference, SOCO’12, Ostrava, Czech Republic, September 5th-7th, 2012, pp.327-336

International Conference, SOCO’12, 7th (Ostrava, Czech Republic, 05-Sep-2012–07-Sep-2012)

Advances in Intelligent Systems and Computing, 188, Springer Berlin

2013

DOI: https://doi.org/10.1007/978-3-642-32922-7_34

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Abstract

Signal processing

Energy efficiency

Data Compression

Huffman Coding

Wireless Sensor Networks

Sensor nodes

Adaptive Entropy Encoder

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.

Details

Title: A simple data compression algorithm for wireless sensor networks
Authors: J G Kolo (Author) - University of Nottingham Malaysia Campus
Li-Minn Ang (Author) - Edith Cowan University
S A Shanmugam (Author) - University of Nottingham Malaysia Campus
D W G Lim (Author) - University of Nottingham Malaysia Campus
K P Seng (Author) - Sunway University
Publication details: Soft Computing Models in Industrial and Environmental Applications: 7th International Conference, SOCO’12, Ostrava, Czech Republic, September 5th-7th, 2012, pp.327-336
Conference details: International Conference, SOCO’12, 7th (Ostrava, Czech Republic, 05-Sep-2012–07-Sep-2012)
Series: Advances in Intelligent Systems and Computing; 188
Publisher: Springer Berlin
Date published: 2013
DOI: 10.1007/978-3-642-32922-7_34; 10.1007/978-3-642-32922-7
ISSN: 2194-5357; 2194-5365; 2194-5357
ISBN: 9783642329227
Organisation Unit: University of the Sunshine Coast, Queensland; School of Science, Technology and Engineering; Engage Research Lab
Language: English
Record Identifier: 99513905202621
Output Type: Conference paper

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