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Published VersionCC BY V3.0, Open Access
Journal article
An adaptive lossless data compression scheme for wireless sensor networks
Journal of Sensors, Vol.2012, pp.1-20
2012
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.
Details
- Title
- An adaptive lossless data compression scheme for wireless sensor networks
- Authors
- Jonathan Gana Kolo (Author) - University of Nottingham Malaysia CampusS Anandan Shanmugam (Author) - University of Nottingham Malaysia CampusDavid Wee Gin Lim (Author) - University of Nottingham Malaysia CampusLi-Minn Ang (Author) - Edith Cowan UniversityKah Phooi Seng (Author) - Sunway University
- Publication details
- Journal of Sensors, Vol.2012, pp.1-20
- Publisher
- Hindawi Limited
- Date published
- 2012
- DOI
- 10.1155/2012/539638
- ISSN
- 1687-725X; 1687-7268; 1687-725X
- Copyright note
- 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.
- Organisation Unit
- University of the Sunshine Coast, Queensland; School of Science, Technology and Engineering; Engage Research Lab
- Language
- English
- Record Identifier
- 99513793902621
- Output Type
- Journal article
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web Of Science research areas
- Engineering, Electrical & Electronic
- Instruments & Instrumentation