Energy-efficient adaptive data compression in wireless sensor networks

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

doi:10.1504/IJSNET.2016.080371

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Energy-efficient adaptive data compression in wireless sensor networks

Journal article

Peer reviewed

Energy-efficient adaptive data compression in wireless sensor networks

Jonathan Gana Kolo, Li-Minn Ang, Kah Phooi Seng, S Anandan Shanmugam and David Wee Gin Lim

International Journal of Sensor Networks, Vol.22(4), pp.229-247

2016

DOI: https://doi.org/10.1504/IJSNET.2016.080371

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Abstract

Signal processing

Energy efficiency

wireless sensor networks

WSNs

data compression

adaptive entropy encoding

AEE

Huffman coding

energy consumption

network lifetime

simulation

In wireless sensor networks (WSNs), a large number of tiny, inexpensive and computable sensor nodes are usually deployed randomly to monitor one or more physical phenomena. The sensor nodes collect and process the sensed data and send the data to the sink wirelessly. Energy consumption is however a serious problem affecting WSNs lifetime. Radio communication is often the major cause of energy consumption in wireless sensor nodes. Thus, applying data compression before transmission can significantly help in reducing the total power consumption of a sensor node. In this paper, we propose an efficient and robust adaptive data compression scheme (ADCS). The proposed scheme independently compresses each block of source data losslessly or lossily on local nodes based on the given application. Simulation results show the merits of the proposed compression scheme in comparison with other recently proposed compression algorithms for WSNs including S-LZW, LEC, MPDC, Two-modal GPC and LTC.

Details

Title: Energy-efficient adaptive data compression in wireless sensor networks
Authors: Jonathan Gana Kolo (Author) - Federal University of Technology Minna
Li-Minn Ang (Author) - 61USC_INST___CSU
Kah Phooi Seng (Author) - Edith Cowan University
S Anandan Shanmugam (Author) - University of Nottingham Malaysia Campus
David Wee Gin Lim (Author) - University of Nottingham Malaysia Campus
Publication details: International Journal of Sensor Networks, Vol.22(4), pp.229-247
Publisher: Inderscience Publishers
Date published: 2016
DOI: 10.1504/IJSNET.2016.080371
ISSN: 1748-1279; 1748-1287; 1748-1279
Organisation Unit: University of the Sunshine Coast, Queensland; School of Science, Technology and Engineering; Engage Research Lab
Language: English
Record Identifier: 99513894502621
Output Type: Journal article

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Collaboration types: Domestic collaboration; International collaboration
Web Of Science research areas: Computer Science, Information Systems; Telecommunications