Wavelet-Based Data Compression Technique for Wireless Sensor Networks
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.
[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.
[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.
@article{"International Journal of Electrical, Electronic and Communication Sciences:51649", author = "P. Kumsawat and N. Pimpru and K. Attakitmongcol and A.Srikaew", title = "Wavelet-Based Data Compression Technique for Wireless Sensor Networks", 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.", volume = "7", number = "5", pages = "502-8", }
