Fast and efficient lossless adaptive compression scheme for wireless sensor networks

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

doi:10.1016/j.compeleceng.2014.06.008

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Fast and efficient lossless adaptive compression scheme for wireless sensor networks

Journal article

Peer reviewed

Fast and efficient lossless adaptive compression scheme for wireless sensor networks

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

Computers and Electrical Engineering, Vol.41, pp.275-287

2015

DOI: https://doi.org/10.1016/j.compeleceng.2014.06.008

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Abstract

Adaptive compression

Compression rates

Compression scheme

Real-life applications

Very low complexity

Wireless sensor network (WSNs)

Wireless sensor network deployment

The number of wireless sensor network deployments for real-life applications has rapidly increased in recent years. However, power consumption is a critical problem affecting the lifetime of wireless sensor networks (WSNs). A number of techniques have been proposed to solve this power problem. Among the proposed techniques, data compression scheme is one that can be used to reduce the volume of data to be transmitted. This paper therefore proposes a fast and efficient lossless adaptive compression scheme (FELACS) for WSNs. FELACS was proposed to enable a fast and low memory compression algorithm for WSNs. FELACS generates its coding tables on the fly and compresses data very fast. FELACS is lightweight, robust to packet losses and has very low complexity. FELACS achieved compression rates of 4.11 bits per sample. In addition, it achieved power savings up to 70.61% using the real-world test datasets.

Details

Title: Fast and efficient lossless adaptive compression scheme for wireless sensor networks
Authors: Jonathan Gana Kolo (Author) - Federal University of Technology Minna
S Anandan Shanmugam (Author) - University of Nottingham Malaysia Campus
David Wee Gin Lim (Author) - University of Nottingham Malaysia Campus
Li-Minn Ang (Author) - Edith Cowan University
Publication details: Computers and Electrical Engineering, Vol.41, pp.275-287
Publisher: Elsevier Ltd
Date published: 2015
DOI: 10.1016/j.compeleceng.2014.06.008
ISSN: 0045-7906; 1879-0755; 0045-7906
Organisation Unit: University of the Sunshine Coast, Queensland; School of Science, Technology and Engineering; Engage Research Lab
Language: English
Record Identifier: 99513889802621
Output Type: Journal article

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Collaboration types: Domestic collaboration; International collaboration
Web Of Science research areas: Computer Science, Hardware & Architecture; Computer Science, Interdisciplinary Applications; Engineering, Electrical & Electronic