An Adaptive Data Aggregation Algorithm in Wireless Sensor Network with Bursty Source
Kumar PADMANABH, Sunil Kumar VUPPALA
DOI: 10.4236/wsn.2009.13029   PDF    HTML     8,373 Downloads   14,715 Views   Citations

Abstract

The Wireless Sensor network is distributed event based systems that differ from conventional communica-tion network. Sensor network has severe energy constraints, redundant low data rate, and many-to-one flows. Aggregation is a technique to avoid redundant information to save energy and other resources. There are two types of aggregations. In one of the aggregation many sensor data are embedded into single packet, thus avoiding the unnecessary packet headers, this is called lossless aggregation. In the second case the sensor data goes under statistical process (average, maximum, minimum) and results are communicated to the base station, this is called lossy aggregation, because we cannot recover the original sensor data from the received aggregated packet. The number of sensor data to be aggregated in a single packet is known as degree of ag-gregation. The main contribution of this paper is to propose an algorithm which is adaptive to choose one of the aggregations based on scenarios and degree of aggregation based on traffic. We are also suggesting a suitable buffer management to offer best Quality of Service. Our initial experiment with NS-2 implementa-tion shows significant energy savings by reducing the number of packets optimally at any given moment of time.

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PADMANABH, K. and VUPPALA, S. (2009) An Adaptive Data Aggregation Algorithm in Wireless Sensor Network with Bursty Source. Wireless Sensor Network, 1, 222-232. doi: 10.4236/wsn.2009.13029.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] B. Krishnamachari, D. Estrin, and S. Wicker, “Modelling data-centric routing in wireless sensor networks,” in Proceed-ings of the IEEE INFOCOM, 2002.
[2] C. Intanagonwiwat, D. Estrin, R. Govindan, and J. Heidemann, “Impact of network density on data aggregation in wireless sensor networks,” in Proceedings of the 22nd International Conference on Distributed Computing Systems (ICDCS’02), July 2002.
[3] V. Erramilli, I. Matta, and A. Bestavros , “On the interaction between data aggregation and topology control in wireless sensor networks,” First Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Net-works, IEEE SECON, pp. 557–565, 2004.
[4] A. Boulis, S. Ganeriwal, and M. B. Srivastava, “Aggregation in sensor networks: An energy-accuracy trade- off,” First IEEE International Workshop Sensor Network Protocols and Appli-cations (SNPA’03), May 2003.
[5] Z. Ye, A. A. Abouzeid, and J. Ai, “Optimal policies for distrib-uted data aggregation in wireless sensor networks,” in Pro-ceedings of 26th Annual IEEE Conference on Computer Communications (INFOCOM’07), Anchorage, Alaska, USA, May 6–12, 2007.
[6] T. He, B. Blum, J. Stankovic, and T. Abdelzaher, “AIDA: Adaptive application independent data aggregation in wireless sensor networks,” ACM Transaction on Sensor Network, 2003.
[7] N. Shrivastava, C. Buragohain, D. Agrawal, and S. Suri, “Me-dians and beyond: New aggregation techniques for sensor net-works,” in Proceedings of the Second ACM Conference on Embedded Networked Sensor Systems (SenSys’04), August 2004.
[8] A. Deligiannakis, Y. Kotidis, and Roussopoulos, “Band-width-constrained queries in sensor networks,” The VLDB Journal, Vol. 17, No. 3, pp. 443–467, 2008.
[9] TinyOS, http://www.tinyos.net/.
[10] K. Padmanabh and R. Roy, “Cost sensitive pushout policy and expelling polices with dynamic threshold for the buffer man-agement in differentiated service switch for versatile traffic,” IEEE International Conference on Networking, Mauritius, April 23–28, 2006.
[11] G. J. Fosdhini and B. Gopinath, “Sharing memory optimally,” IEEE Transaction on Communication, Vol. 31, No. 3, pp. 352–360, March 1983.
[12] Network Simulator 2, http://www.isi.edu/nsnam/ns/.

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