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Median Predictor based Data Compression Algorithm for Wireless Sensor Network
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 24 - Number 6 |
| Year of Publication: 2011 |
| Authors: Ashish K. Maurya, Dinesh Singh |
10.5120/2961-3942
|
Ashish K. Maurya, Dinesh Singh . Median Predictor based Data Compression Algorithm for Wireless Sensor Network. International Journal of Computer Applications. 24, 6 ( June 2011), 15-18. DOI=10.5120/2961-3942
Abstract
Large scale wireless sensor networks (WSNs) have emerged as the latest trend in revolutionizing the paradigm of collecting and processing data in diverse environments. Its advancement is fueled by development of tiny low cost sensor nodes which are capable of sensing, processing and transmitting data. Due to the small size of sensor nodes there are various resource constraints. It is the severe energy constraints and the limited computing resources that present the major challenge in converting the vision of WSNs to reality. In this paper, we propose a simple and efficient data compression algorithm which is lossless and particularly suited to the reduced memory and computational resources of a wireless sensor networks node. The proposed data compression algorithm gives good compression ratio for highly correlated data. Simulations for the proposed data compression algorithm are performed on TOSSIM.
References
- Akyildiz, I.F.; Weilian Su; Sankarasubramaniam, Y.; Cayirci, E.;, "A survey on sensor networks," Communications Magazine, IEEE , vol.40, no.8, pp. 102- 114, Aug 2002.
- Kimura, N.; Latifi, S.; , "A survey on data compression in wireless sensor networks," International Conference on Information Technology: Coding and Computing (ITCC 2005), vol.2, pp. 8- 13, April 2005
- M. Hans and R. W. Schafer, “Lossless compression of digital audio,” IEEE Signal Processing Magazine, vol.18, no.4, pp. 21–32, July 2001.
- Kenneth. C. Barr and Krste. Asanovi´c, “Energy-aware Lossless Data Compression,” ACM Transactions on Computer Systems, Vol. 24, No. 3, pp. 250–291, August 2006.
- Pradhan S., Kusuma J., and Ramchandran K., “Distributed Compression in a Dense Microsensor Network,” IEEE Signal Processing Magazine, vol. 19, no. 2, pp. 51-60, 2002.
- Y. Zhang and J. Li, “Efficient seismic response data storage and transmission using ARX model-based sensor data compression algorithm,” Earthquake Engineering and Structural Dynamics, vol. 35, pp. 781–788, 2006.
- C. M. Sadler and M. Martonosi, “Data Compression Algorithms for Energy-Constrained Devices in Delay Tolerant Networks,” in Proceedings of the 4th International Conference on Embedded Networked Sensor Systems (SenSys), 2006.
- N. Tsiftes, A. Dunkels, and T. Voigt, “Efficient Sensor Network Reprogramming through Compression of Executable Modules,” in Proceedings of the 5th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON), 2008.
- H. Ju and L. Cui, “EasiPC: A Packet Compression Mechanism for Embedded WSN,” in Proceedings of the 11th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA), 2005
- A. Reinhardt, M. Hollick, and R. Steinmetz, “Stream-oriented Lossless Packet Compression in Wireless Sensor Networks,” in Proceedings of the Sixth Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON), 2009.
- Francesco Marcelloni and Massimo Vecchio, “A Simple Algorithm for Data Compression in Wireless Sensor Networks,” IEEE Communications Letters, Vol. 12, No. 6, June 2008.
- David Gay, Philip Levis, David Culler, Eric Brewer, “nesC 1.2 Language Reference Manual,” August 2005.
- Phillip Levis, “TinyOS Programming,” June 28, 2006.
- Philip Levis and Nelson Lee, “TOSSIM: A Simulator for TinyOS Networks,” September 17, 2003.
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