Wavelet-Based Data Compression Technique for Wireless Sensor Networks
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Wavelet-Based Data Compression Technique for Wireless Sensor Networks

Authors: P. Kumsawat, N. Pimpru, K. Attakitmongcol, A.Srikaew

Abstract:

In this paper, we proposed an efficient data compression strategy exploiting the multi-resolution characteristic of the wavelet transform. We have developed a sensor node called “Smart Sensor Node; SSN". The main goals of the SSN design are lightweight, minimal power consumption, modular design and robust circuitry. The SSN is made up of four basic components which are a sensing unit, a processing unit, a transceiver unit and a power unit. FiOStd evaluation board is chosen as the main controller of the SSN for its low costs and high performance. The software coding of the implementation was done using Simulink model and MATLAB programming language. The experimental results show that the proposed data compression technique yields recover signal with good quality. This technique can be applied to compress the collected data to reduce the data communication as well as the energy consumption of the sensor and so the lifetime of sensor node can be extended.

Keywords: Wireless sensor network, wavelet transform, data compression, ZigBee, skipped high-pass sub-band.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1057373

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References:


[1] N. Watthanawisuth, N. Tongrod, T. Kerdcharoen and A.Tuantranont, "Real-Time Monitoring of GPS-Tracking Tractor Based on ZigBee Multi-Hop Mesh Network," In Proc. the Electrical Engineering/Electronics Computer Telecommunications and Information Technology, Vol. 1, pp. 580-583, 2010.
[2] N. Kimura and S. Latifi, "A Survey on Data Compression in Wireless Sensor Networks," In Proc. the Information Technology: Coding and Computing, Vol. 2, pp:8 - 13, 2005.
[3] A. Kulakov and D. Davcev, "Intelligent Data Acquisition and Processing Using Wavelet Neural Networks," In Proc. IEEE Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, Vol. 1, pp. 491-494, 2005.
[4] A. Goh, S. Craciun, S. Rao, D. Cheney, K. Gugel, J. C. Sanchez, J. C. Principe, "Wireless Transmission of Neuronal Recordings Using a Portable Real-Time Discrimination/Compression Algorithm," In Proc. the 30th Annual International Conference on Engineering in Medicine and Biology Society, pp:4439 - 4442, 2008.
[5] M. Nasri, A. Helali, H. Sghaier, and H. Maaref, "Energy-Efficient Wavelet Image Compression in Wireless Sensor Network," In Proc. the Communication in Wireless Environments and Ubiquitous Systems: New Challenges (ICWUS), pp. 1 - 7, 2010.
[6] N. Kimura and S. Latifi, "A survey on data compression in wireless sensor networks," In Proc. the Information Technology: Coding and Computing, Vol. 2, pp:8 - 13, 2005.
[7] E. Chichi, H. Guyennet and J. Friedt, "K-RLE : A New Data Compression Algorithm for Wireless Sensor Network," In Proc. the 2009 Third International Conference on Sensor Technologies and Applications, Vol. 1, pp. 502-507, 2009.
[8] M. Nasri, A. Helali, H. Sghaier and H. Maaref, "Adaptive image transfer for wireless sensor networks (WSNs)" In Proc. 2010 International Conference on Design & Technology of Integrated Systems in Nanoscale Era, Vol. 1, pp:1 - 6, 2010.
[9] E. Manhas, G. Brante, R. Souza and M. Pellenz, "Energy-Efficient Cooperative Image Transmission Over Wireless Sensor Networks," In Proc. the 2012 IEEE Wireless Communications and Networking Conference : Mobile and Wireless Networks, Vol. 2, pp. 2014-2019, 2012.
[10] N.Rajput, N.Gandhi and L. Saxena, "Wireless Sensor Networks: Apple farming in Northern India," In Proc. 2012 Fourth International Conference on Computational Intelligence and Communication Networks, Vol. 1, pp. 218-221, 2012.
[11] M. Kohvakka, M. Kuorilehto, M. Hännikäinen and T. D. Hämäläinen, "Performance Analysis of IEEE 802.15.4 and ZigBee for Large-Scale Wireless Sensor Network Applications" In. Proc. the 3rd ACM international workshop on Performance evaluation of wireless ad hoc, sensor and ubiquitous networks, Vol. 1, pp.45-48, 2006.
[12] R. V. Kulkarni and G. K. Venayagamoorthy,"Computational Intelligence in Wireless Sensor Networks: A Survey," IEEE Communications Surveys & Tutorials, Vol. 13, No. 1, pp. 68-96, 2011.
[13] S.G. Mallat, "A Theory for Multiresolution Signal Decomposition: The Wavelet Representation," IEEE Trans. Pattern Anal. Mach. Intell. Vol. 11, pp. 674-693, 1989.
[14] FiO Std evaluation board web site, https://www.aimagin.com/fiostd. html.
[15] B. Arvinti, C. Nafornita, I. Alexandru and M. Costache "ECG Signal Compression Using Wavelets.Preliminary Results," In. Proc. 2011 10th International Symposium on Signals, Circuits and Systems, Vol. 1, pp. 1-4, 2011.