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Data Propelling Scheme for Node Level Congestion Control in WSNs

N. Prabakaran, K. Geetha, K. Janani


The rising data centric Wireless sensor network (WSN) is recently emerging technology, which offers the key to isotonic situation in an un-interruptible environment application. It has the ability of keen observation and ties the information with outside world. WSN tenuously collects the dense amount of data, further communicates with the sink through various intermediate nodes. It delivers reckonable response, when unpredictable variation occurs in the environment. Rushing of the enormous data directs to overcrowd in the routing path, which affects vibrant strength of the network. Many of the existing schemes focused on link level congestion. We propose data propelling scheme, which discusses the congestion free environment in node level congestion. Once congestion notification bit is set, new data buffer node awakened, which is near-by to congested node. After its activation, all the data are re-directed to the data buffer and retrieved back in need even at unusual changes occurred further CN bit is cleared. Aspire is, make processing rate which is to be equal to transmitting rate to avoid funneling effect. Our scheme is not consuming too much of energy of new data buffers and resources. It annotates that nodes are intended for working for long time without human intervention. Further our scheme is concentrating on congestion free critical environmental applications, otherwise which drastically decrease the performance of the network.


Data Propelling, Congestion Control, Node Level Congestion, Sink.

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Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, “A survey on sensor networks,” IEEE Commun. Mag., vol. 40, no. 8, pp. 102–104, Aug. 2002..

Vivek Deshpande, Prachi Sarode, Sambhaji Sarode,”EDCAM-Early Detection Congestion Avoidance Mechanism “International journal of Computer Application 7(2)11-14, Number 18, Article 6

Y.Sankarsubramaniam,OzgurBAkan,I.F.Akyildiz,”ESRT: Event to sink reliable transport in Wireless Sensor Network”,Proc. of ACM MobiHoc‟03

J. Kulik, W. Rabiner, and H. Balakrishnan, “Adaptive protocols for information dissemination in wireless sensor networks,” in Proc. ACM MobiCom, Seattle, WA, Aug. 1999, pp. 174–185

B. Hull, K. Jamieson, and H. Balakrishnan, “Mitigating congestion in wireless sensor networks,” in Proc. 2nd ACM Conf. Embedded Baltimore, MD, Nov. 2004

S. Chen, Y. Fang, and Y. Xia, “Lexicographic maxmin fairness for data collection in wireless sensor networks,” IEEE Trans. Mobile Comput., vol. 6, no. 7, pp, Jul. 2007

.Janani.K, V.R.SarmaDhulipala”A WSN Based Framework for Human Health Monitoring” IEEE International Conferenceon Devices and Communication ICDECOM.2011.5738453, pages(1-5), IEEE2011

C.-Y. Wan, S. B. Eisenman, and A. T. Campbell, “CODA: Congestion detection and avoidance in sensor networks,” in Proc. ACM SenSys, Nov. 2003

Su-yun zhao; Tsang, yeung.D.S, “Fuzzy matrix Computation for fuzzy information system to reduce Attributes” in proc of IEE 2006on machine learning and cybernatics

N.Prabakaran, B.Shanmugaraja, R.Prabakaran, V.R.Sarma Dhulipala “Rate optimization scheme for node level congestion in WSNs”, on ICDeCOM.2011.5738548, pages(1-5) in IEEE 2011.

N.Prabakaran, B.Shanmugaraja, R.Prabakaran, “Queue Reloading scheme for congestion levelling in WSNs” on ICDeCOM.2011.5738568,pages(1-5) IEEE 2011

B.Shanmugaraja, N.Prabakaran, V.R.Sarma Dhulipala “Modified GPSR based optimal routing algorithm for reliable communication in WSNs” on ICDeCOM2011.5738563. pages(1-5) in IEEE 2011.


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