CFP last date
20 June 2024
Reseach Article

Fuzzy Application for Tracking Heterogeneous Sensor Node to Prolong System Lifetime in WSN Word Template

Published on April 2012 by Raju Dutta, Sajal Saha, Asish K. Mukhopadhyay
International Conference on Recent Advances and Future Trends in Information Technology (iRAFIT 2012)
Foundation of Computer Science USA
IRAFIT - Number 1
April 2012
Authors: Raju Dutta, Sajal Saha, Asish K. Mukhopadhyay
84d5cd8b-5538-4318-a61c-f554b2d890de

Raju Dutta, Sajal Saha, Asish K. Mukhopadhyay . Fuzzy Application for Tracking Heterogeneous Sensor Node to Prolong System Lifetime in WSN Word Template. International Conference on Recent Advances and Future Trends in Information Technology (iRAFIT 2012). IRAFIT, 1 (April 2012), 12-18.

@article{
author = { Raju Dutta, Sajal Saha, Asish K. Mukhopadhyay },
title = { Fuzzy Application for Tracking Heterogeneous Sensor Node to Prolong System Lifetime in WSN Word Template },
journal = { International Conference on Recent Advances and Future Trends in Information Technology (iRAFIT 2012) },
issue_date = { April 2012 },
volume = { IRAFIT },
number = { 1 },
month = { April },
year = { 2012 },
issn = 0975-8887,
pages = { 12-18 },
numpages = 7,
url = { /proceedings/irafit/number1/5847-1003/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Recent Advances and Future Trends in Information Technology (iRAFIT 2012)
%A Raju Dutta
%A Sajal Saha
%A Asish K. Mukhopadhyay
%T Fuzzy Application for Tracking Heterogeneous Sensor Node to Prolong System Lifetime in WSN Word Template
%J International Conference on Recent Advances and Future Trends in Information Technology (iRAFIT 2012)
%@ 0975-8887
%V IRAFIT
%N 1
%P 12-18
%D 2012
%I International Journal of Computer Applications
Abstract

Mobility of sensor node in Wireless Sensor Network (WSN) is one of the key advantages of wireless over fixed communication system. But to track the sensor node in the heterogeneous network is more challenging and difficulties. In heterogeneous system, generally power consumption is more then homogeneous system. Thus, tracking the location of sensor node is not only one of the challenges for location management but to prolong the system lifetime is also very much important in WSN. Fuzzy application is a new era in communication system. Using fuzzy in heterogeneous system, can easily track the sensor node and consequently prolong the system lifetime. In this paper we introduce a movement pattern learning strategy system to track the node's movement using adaptive fuzzy logic. Every node of different category identified as a cell in a location. Here fuzzy inferences system extracts pattern from the past data records as occupying cell number, date and time of sensor node of particular type. Here in this paper this strategy has been implemented and we propose a mathematical model, that model has been verified with real time data. This mechanism reduces sensor node's location tracking cost. All together overall it prolong the system lifetime Here in this paper we have discussed and proposed a mathematical model to find an optimal solution to optimize energy consumption of the sensor node and to maximize system life time. Through an extensive simulation results show that the proposed model has good performances in the aspects of energy consumption and efficiency of the system network to prolong the system life time.

References
  1. Akyildiz,I.F., Weilian, S., Sankarasubramaniam, Y.,and Cayirci, E. 2011 "A survey on sensor networks", Communications Magazine, IEEE, 40(8), 102 - 114.
  2. Heinzelman, R. 2000 "Energy Scalable Algorithms and Protocols for Wireless Sensor Networks", in Proceedings of the International Conference on Acoustics, Speech, and Signal Processing (ICASSP'00), Turkey, 773-776.
  3. Wang, A. 2001 "Energy-Scalable Protocols for Battery: Operated Micro Sensor Networks", Computer Journal of VLSI Signal Processing, 29(3), 223-237.
  4. Ghosh, S., Razouqi, Q., Schumacher, H., and Celmins, A.1998 "A Survey of Recent Advances in Fuzzy Logic in Telecommunications Networks and New Challenges", Computer Journal of IEEE Transactions on Fuzzy Systems, 6(3), 443-447.
  5. Nikaein, N., Bonnet, C. 2002 "ALM Adaptive Location Management Model Incorporating Fuzzy Logic for Mobile Ad Hoc Networks", in Proceeding of Med Hoc Net, Italy, 1489-1499.
  6. Simon, Y. 2001 "A fuzzy logic approach to fire detection in aircraft dry bays and engine compartments", IEEE Transaction on Industrial Electronics, 47(5), 1161–1171.
  7. Li, Z. B., Zhou, H., 2004 "Research on the application of fuzzy data fusion to cable fire detecting system", in Proceedings of the Third International Conference on Machine Learning and Cybernetics, 4, 2083– 2085.
  8. Bao, H., Li, J., Zeng, X., and Zhang, J. 2003 "A fire detection system based on intelligent data fusion technology", in Proceedings of the Third International Conference on Machine Learning and Cybernetics, 2, 1096– 1101
  9. Mukhopadhyay, A. K. et al , 2009 "An Efficient Call Admission Control Scheme on Overlay Networks Using Fuzzy Logic", 3rd International Symposium on Advance Networks and Telecommunication System (IEEE ANTS), 1-3.
  10. Sivanandam, S. N., Sumathi, S., and Deepa, S. N. 2007 "Introduction to Fuzzy Logic using MATLAB", Springer-Verlag Berlin Heidelberg.
  11. Majumdar, K., Das, N. 2005 "Mobile User Tracking Using A Hybrid Neural Network ", Kluwer Academic publisher Hingham, MA, USA, 275-284.
  12. Majumdar, K., Das, N. 2003 "Neural Networks for location management in mobile cellular communication system", TENCON 2003, conference on convergent technologies for Asia-Pacific,2, 647-651.
  13. Misra, I. S. et. al. 2002 "Intelligent paging strategy in 3G personal communication system", EurAsia-ICT 2002,LNCS, Springer Berlin / Heidelberg, 899-906.
  14. Amar, J., Singh, P., and Karnan, M. 2010 "Intelligent location management for UMTS networks using fuzzy neural networks", Journal of Engineering and Technology Research, 2 (1), 001-012.
  15. Akoush, S., Sameh, A. 2007 "Movement Prediction Using Bayesian Learning for Neural Networks", proceedings of Second International Conference on Systems and Networks Communications (ICSNC 2007), 6-10.
  16. Fakhreddine, O., Karray, D., and Silva, C., "Mobile position estimation using RBF network in CDMA cellular systems", from book Soft Computing and Intelligent Systems Design Theory, Tools and Applications, 522-532.
  17. Ross, T. J. 1997 Fuzzy logic with engineering applications, New York, McGraw-Hill Inc.
  18. Bowles, J., Pelaez, C. E. 1995 "Application of fuzzy logic to reliability engineering", in Proceeding of the IEEE, 83( 3), 435–449.
  19. Kenarangui, R. 1991 "Event-tree analysis by fuzzy probability", IEEE Transactions on Reliability, 40(1), 120–124.
  20. Bouzaouache, H., Braiek N.B. 2008 "On the stability analysis of nonlinear systems using polynomial Lyapunov functions", Journal of Mathematics and Computers in Simulation, Elsevier Science Publishers,76(5-6), 316-329.
  21. Kolokolov, A. A., Sykov, A. I. 1975 "Instability in the higher modes of a nonlinear equation", Journal of Applied Mechanics and Technical Physics, Springer New York, 16(4), 519-522.
Index Terms

Computer Science
Information Sciences

Keywords

Sensor Nodes System Life Time Fuzzy Logic Wsn Node Deployment Fuzzy Inference System