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Reseach Article

Energy Efficient Routing in Wireless Sensor Networks with a Dynamic Sink based Congestion Control Protocol

Published on August 2012 by Medha Sanjay Asurlekar, R. D. Patane
International Conference on Advances in Communication and Computing Technologies 2012
Foundation of Computer Science USA
ICACACT - Number 1
August 2012
Authors: Medha Sanjay Asurlekar, R. D. Patane
f6be8af6-d6c7-4ce1-a194-e9e368a8e336

Medha Sanjay Asurlekar, R. D. Patane . Energy Efficient Routing in Wireless Sensor Networks with a Dynamic Sink based Congestion Control Protocol. International Conference on Advances in Communication and Computing Technologies 2012. ICACACT, 1 (August 2012), 16-22.

@article{
author = { Medha Sanjay Asurlekar, R. D. Patane },
title = { Energy Efficient Routing in Wireless Sensor Networks with a Dynamic Sink based Congestion Control Protocol },
journal = { International Conference on Advances in Communication and Computing Technologies 2012 },
issue_date = { August 2012 },
volume = { ICACACT },
number = { 1 },
month = { August },
year = { 2012 },
issn = 0975-8887,
pages = { 16-22 },
numpages = 7,
url = { /proceedings/icacact/number1/7968-1004/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Advances in Communication and Computing Technologies 2012
%A Medha Sanjay Asurlekar
%A R. D. Patane
%T Energy Efficient Routing in Wireless Sensor Networks with a Dynamic Sink based Congestion Control Protocol
%J International Conference on Advances in Communication and Computing Technologies 2012
%@ 0975-8887
%V ICACACT
%N 1
%P 16-22
%D 2012
%I International Journal of Computer Applications
Abstract

Congestion in wireless sensor network occurs mainly due to two reasons --when multiple nodes want to transmit data through the same channel at a time or when the routing node fails to forward the received data to the net routing node. Congestion in wireless sensor network cause packet loss and due to this packet loss throughput may be lowered and also, congestion leads to excessive energy consumption. Therefore congestion has to be controlled to prolong the sensor nodes lifetime, in terms of throughput and packet loss ratio along with the packet delay. This paper proposes an dynamic sink based congestion control protocol named dynamic sink based congestion control protocol (DSCCP) for wireless sensor networks. Congestion and data loss mainly occurs in the vicinity of the static sink. Dynamic sink is responsible for collecting data from the sensor nodes located in their vicinity ,thus avoiding data flow to a single data collection point, e. g. a static sink is the main cause of congestion , data loss and reduced lifetime of the sensor network. Also in proposed scheme we used the in-network storage model that is used to ensure data persistency under congestion on WSN. Through simulation we show the effectiveness of the given routing scheme in terms of congestion avoidance and increased lifetime of the WSN.

References
  1. Majid I. Khan, Wilfried N. Gansterer, Guenter Haring, "In- network storage model for data persistence under congestion in wireless sensor network". In Proceedings of the First International Conference on Complex, Intelligent and Software Intensive Systems (CISIS'07), 2007, pp. 221- 228.
  2. Shigang Chen, Na Yang, "Congestion avoidance based on lightweight buffer management in sensor networks," IEEE Transactions on Parallel and Distributed Systems, Sept 2006. vol. 17, no. 9, pp. 934-946.
  3. Fan, K. , Liu, S. , and Sinha, P. "Scalable data aggregation for dynamic events in sensor networks". In Proceedings of the 4th international Conference on Embedded Networked Sensor Systems (Boulder, Colorado, USA, October 31 - November 03, 2006). SenSys '06. ACM Press, New York, NY, pp. 181-194.
  4. Sharaf, M. A. , Beaver, J. , Labrinidis, A. , and Chrysanthis, P. K. "TiNA: a scheme for temporal coherency-aware in- network aggregation". In Proceedings of the 3rd ACM international Workshop on Data Engineering For Wireless and Mobile Access. San Diego, CA, USA, September 19, 2003. MobiDe '03. ACM Press, New York, NY, pp. 69-76.
  5. Laura Galluccio, Andrew T. Campbell, Sergio Palazzo, "Concert: aggregation-based congestion control for sEnsoR networks". In Proceedings of the 3rd international conference on Embedded networked sensor systems 2005, Conference On Embedded Networked Sensor Systems, San Diego, California, USA, pp. 274-275.
  6. Barton, R. J. Zheng, R. "Order-Optimal Data Aggregation in Wireless Sensor Networks Using Cooperative Time- Reversal Communication". 40th Annual Conference on Information Sciences and Systems, 22-24 March 2006, Princeton, NJ, pp. 1050-1055.
  7. Gao, J. , Guibas, L. , Milosavljevic, N. , and Hershberger, J. "Sparse data aggregation in sensor networks". In Proceedings of the 6th international Conference on information Processing in Sensor Networks (Cambridge, Massachusetts, USA, April 25 - 27, 2007). IPSN '07. ACM Press, New York, NY, pp. 430-439.
  8. Alberto Cerpa and Deborah Estrin. "ASCENT: Adaptive Self-Configuring sEnsor Networks Topologies". In the IEEE Transactions on Mobile Computing Special Issue on Mission-Oriented Sensor Networks, July- September 2004, vol. 3, no. 3, pp. 272-285.
  9. Zhu, J. , Hung, K. , and Bensaou, B. "Tradeoff between network lifetime and fair rate allocation in wireless sensor networks with multi-path routing". In Proceedings of the 9th ACM international Symposium on Modeling Analysis and Simulation of Wireless and Mobile Systems (Terromolinos, Spain, October 02 - 06, 2006). MSWiM '06. ACM Press, New York, NY, pp. 301-308.
  10. Wan, C. , Eisenman, S. B. , and Campbell, A. T. "CODA: congestion detection and avoidance in sensor networks". In Proceedings of the 1st international Conference on Embedded Networked Sensor Systems (Los Angeles, California, USA, November 05 - 07, 2003). SenSys '03. ACM Press, New York, NY, pp. 266-279.
  11. Akan, Ö. B. and Akyildiz, I. F. "Event-to-sink reliable transport in wireless sensor networks. " IEEE/ACM Trans. Network 13, 5(Oct. 2005), pp. 1003-1016.
  12. Wang, C. Li, B. Sohraby, K. Daneshmand, M. Hu, Y. , "Upstream congestion control in wireless sensor networks through cross-layer optimization," IEEE journal on selected areas in communications, vol. 25, no. 4, 2007.
  13. Chatzigiannakis, I. , Kinalis, A. , and Nikoletseas, S. "Sink mobility protocols for data collection in wireless sensor networks. " In Proceedings of the international Workshop on Mobility Management and Wireless Access (Terromolinos, Spain, October 02 - 02, 2006). MobiWac '06. ACM Press, New York, NY, 52-59.
  14. J. Luo and J. -P. Hubaux. "Joint mobility and routing for lifetime elongation in wireless sensor networks. " In Proceedings of the 24th Annual Conference of the IEEE Communications Societies (INFOCOM'05), FL, USA.
  15. J. Luo, J. Panchard, M. Piorkowski, M. Grossglauser, and J. -P. Hubaux. MobiRoute: Routing towards a Mobile Sink for Improving Lifetime in Sensor Networks. In International Conference on Distributed Computing in Sensor Systems (DCOSS'06), San Francisco, CA, USA.
  16. Prem Prakash Jayaraman, Arkady Zaslavsky, Jerker Delsing. "Sensor data collection using heterogeneous mobile devices. " ICPS'07: IEEE International Conference on Pervasive Services July 15-20, 2007, Istanbul, Turkey.
  17. Sun, K. , Peng, P. , Ning, P. , and Wang, C. "Secure Distributed Cluster Formation in Wireless Sensor Networks". In Proceedings of the 22nd Annual Computer Security Applications Conference (December 11-15, 2006). ACSAC. IEEE Comp Society, WashingtonDC,pp. 131-140.
  18. He, Y. , Zhang, Y. , Ji, Y. , and Shen, X. "A new energy efficient approach by separating data collection and data report in wireless sensor networks". In Proceeding of the 2006 international Conference on Communications and Mobile Computing (Vancouver, British Columbia, Canada, July 03 - 06, 2006). IWCMC '06. ACM Press, New York, NY, 1165-117
Index Terms

Computer Science
Information Sciences

Keywords

Congestion Control Energy Efficient Routing Dynamic Sink Wireless Sensor Networks