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Journal of Sensors
Volume 2012 (2012), Article ID 539638, 20 pages
http://dx.doi.org/10.1155/2012/539638
Research Article

An Adaptive Lossless Data Compression Scheme for Wireless Sensor Networks

1Department of Electrical and Electronics Engineering, The University of Nottingham, Malaysia Campus, Jalan Broga, Selangor Darul Ehsan, 43500 Semenyih, Malaysia
2School of Engineering, Edith Cowan University, Joondalup, WA 6027, Australia
3School of Computer Technology, Sunway University, 5 Jalan Universiti, Bandar Sunway, Selangor, 46150 Petaling Jaya, Malaysia

Received 4 July 2012; Revised 10 September 2012; Accepted 10 September 2012

Academic Editor: Eugenio Martinelli

Copyright © 2012 Jonathan Gana Kolo et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Energy is an important consideration in the design and deployment of wireless sensor networks (WSNs) since sensor nodes are typically powered by batteries with limited capacity. Since the communication unit on a wireless sensor node is the major power consumer, data compression is one of possible techniques that can help reduce the amount of data exchanged between wireless sensor nodes resulting in power saving. However, wireless sensor networks possess significant limitations in communication, processing, storage, bandwidth, and power. Thus, any data compression scheme proposed for WSNs must be lightweight. In this paper, we present an adaptive lossless data compression (ALDC) algorithm for wireless sensor networks. Our proposed ALDC scheme performs compression losslessly using multiple code options. Adaptive compression schemes allow compression to dynamically adjust to a changing source. The data sequence to be compressed is partitioned into blocks, and the optimal compression scheme is applied for each block. Using various real-world sensor datasets we demonstrate the merits of our proposed compression algorithm in comparison with other recently proposed lossless compression algorithms for WSNs.