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A Novel Energy Aware Routing Approach using ANN Technique with Data Fusion in WSN: Review

by Pooja Singh, Vikas Pareek, Anil K. Ahlawat
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 143 - Number 10
Year of Publication: 2016
Authors: Pooja Singh, Vikas Pareek, Anil K. Ahlawat
10.5120/ijca2016910376

Pooja Singh, Vikas Pareek, Anil K. Ahlawat . A Novel Energy Aware Routing Approach using ANN Technique with Data Fusion in WSN: Review. International Journal of Computer Applications. 143, 10 ( Jun 2016), 18-22. DOI=10.5120/ijca2016910376

@article{ 10.5120/ijca2016910376,
author = { Pooja Singh, Vikas Pareek, Anil K. Ahlawat },
title = { A Novel Energy Aware Routing Approach using ANN Technique with Data Fusion in WSN: Review },
journal = { International Journal of Computer Applications },
issue_date = { Jun 2016 },
volume = { 143 },
number = { 10 },
month = { Jun },
year = { 2016 },
issn = { 0975-8887 },
pages = { 18-22 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume143/number10/25113-2016910376/ },
doi = { 10.5120/ijca2016910376 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:46:25.711798+05:30
%A Pooja Singh
%A Vikas Pareek
%A Anil K. Ahlawat
%T A Novel Energy Aware Routing Approach using ANN Technique with Data Fusion in WSN: Review
%J International Journal of Computer Applications
%@ 0975-8887
%V 143
%N 10
%P 18-22
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Since WSN having a limitation of the limited battery life time and if the battery will die soon i.e. Network has a finite lifespan. The most famous issue facing network designers in wireless networks is to maximize network life. In wireless communication devices, due to resource constraints sensors evidence and delivery of reliable data is a difficult task. The motivation behind this study is the some critical limitation of energy aware routing protocols. Such as; it’s not easy to communicate to Base Station (BS) for that Cluster Head (CH) which is at maximum distance from Base Station therefore to make a novel mechanism by which long distance/route CH can be communicate with fast time with minimum energy consumptions to the base station (BS), here introduced data fusion concept. In WSN can be deployed a fusion point for accurate decision. This study includes directing the efficient use of artificial intelligent protocol with data fusion concept.

References
  1. Shen C, Srisathapornphat C and Jaikaeo C (2001), Sensor information networking architecture and applications, IEEE Perspective Communication, pp 52-59.
  2. Culler D, Estrin D and Srivastava M (2004), Overview of sensor networks, IEEE Computer Society, pp 41-49.
  3. Larios D F, Barbancho J, Rodriguez G, Sevillano J L, Molina F J and Leon C (2012), “Energy efficient wireless sensor network communications based on computational intelligent data fusion for environmental monitoring,” IET Communications, vol. 6, no. 14, pp. 2189–2197.
  4. Li, Xiao-Hui, and Zhi-Hong Guan, “energy aware routing in WSN Using local betweenness centrality”, International Journal of Distributed Sensor Networks Volume 2013 (2013), Article ID 307038, pages 9. 2013.
  5. Mainwaring A, Culler D, Polastre J, Szewczyk R and Anderson J (2002), Wireless Sensor networks for habitat monitoring, in WSNA.
  6. Shah R and Rabaey J (2002), “Energy aware routing for low energy adhoc sensor networks,” in Proceedings of the IEEE Wireless Communications and Networking Conference (IEEE WCNC '02), pp. 350–355, Orlando, Fla, USA.
  7. XH Li, SH Hong, KL Fang; “Location-based self-adaptive routing algorithm for wireless sensor networks in home automation”, EURASIP Journal on Embedded Systems, 2011 – Springer, open access research article.
  8. Li X H, Hong S H, and Fang K (2011), “A greedy and heuristic routing algorithm for wireless sensor networks in home automation,” IET Communications, vol. 5, no. 13, pp. 1797–1805.
  9. M. Umadevi and M. Devapriya Open Access An Enhanced Ant Colony Based Approach to Optimize the Usage of Critical Node in Wireless Sensor Networks”, Graph algorithms, high performance Implementation and its applications (ICGHIA 2014), procedia computer science; volume 47, 2015, pages 452-459
  10. Bisnik N, Abouzeid A and Isler V (2006), Stochastic event capture using mobile sensors subject to a quality metric, In MobiCom.
  11. Cui G and Mohapatra P (2004), Power conservation and quality of surveillance in target tracking sensor networks, In MobiCom.
  12. Chair Z and Varshney P (2000), Optimal data fusion in multiple sensor detection systems, IEEE Trans Acrosp. Electron. System, 22 (1).
  13. Enami N, Askari Moghadam R, Haghighat A (2010), A survey on application of neural networks in Energy Conservation of wireless sensor networks, In Recent trends in wireless and mobile networks WIMO, 2010 Proceedings, Ankara, Turkey, pp 283-294.
  14. Kulakov A, Davcev D and Trajkovski G (2005), Application of wavelet neural networks in wireless sensor networks, 6th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing and First ACIS International Workshop on Self Assembling Wireless Networks, p 262-267.
  15. Aslam N, Philips W, Robertson W and Siva Kumar S H (2010), A multi criterion optimization technique for energy efficient cluster formation in wireless sensor networks, In Information Fusion, Elsevier.
  16. Anatasi G, Conti M and Pasarrella A (2009), Energy conservation in wireless sensor networks a survey, In Adhoc Networks, Volume 7, Issue 3, Elsevier, pp 537-568.
  17. Liu M, Cao J, Chen G and Wang X (2009), An Energy-Aware Routing Protocol in Wireless Sensor Networks, Sensors, Vol-9, pp 445-462.
  18. Baranidharan B and Shanthi B (2010), A Survey on Energy Efficient Protocols for Wireless Sensor Networks, International Journal of Computer Applications, 11(10).
  19. Enami N, Moghadam A R, Dadashtabar K and Hoseini M (2010), Neural Network Based Energy Efficiency in Wireless Sensor Networks: A Survey, International Journal of Computer Science and Engineering Survey, 1(1).
  20. Singh K S, Singh P M and Singh K D (2010), Routing Protocols in Wireless Sensor Networks- A Survey, International Journal of Computer Science and Engineering Survey, 1(2).
  21. Padmanabhan, K., and Kamalakkannan, P., (2011), “A Study on Energy Efficient Routing Protocols in Wireless Sensor Networks”, European Journal of Scientific Research, Vol. 60, No. 4, pp. 499-511.
  22. Nagarajan M and Geetha T (2012), Wireless Sensor Network’s Life Time Enhancement With Aid Of Data Fusion, Leach-C And Spreading Techniques, I J I T E , 3(1-2), pp 375-380.
  23. Nimbalkar K J (2012), Use of Neural Networks in WSNs: A Survey, International Journal of advancement in electronics and computer engineering, 1(3), pp 93-98.
  24. Nivetha G (2012), Energy Optimization Routing Techniques in Wireless Sensor Networks, International Journal of Advanced Research in Computer Science and Software Engineering, 2(7).
  25. Amri S and Kaddachi L M (2014), SOM Based Energy-Efficient Multi-hop Hierarchical Routing Protocol for Wireless Networks, NNGT Int. J. of. Artificial Intelligence, Vol-1.
  26. Kashani A, Mosavian I and Mahriyar H (2014), A Method for Reduction of Energy Consumption in Wireless Sensor Networks with using Neural Networks, Indian Journal of Fundamental and Applied Life Sciences, 4(S3), pp 1043-1050.
  27. Mondal K R and Sarddar D (2014), Data-Centric Routing Protocols in Wireless Sensor Networks: A Survey, COMPUSOFT: An International Journal of Advanced Computer Technology, 3(2).
  28. Kumar A S and Illango P (2015), Data Funnelling in Wireless Sensor Networks: A Comparative Study, Indian Journal of Science and Technology, 8(5), pp 472-480.
  29. Gurbani P, Acharya H and Jain A. (2016), Hierarchical Cluster Based Energy Efficient Routing Protocol for Wireless Sensor Networks: A Survey, International Journal of Computer Science and Information Technologies, 7(2), pp 682-687.
  30. Yadav S G S and Chitra A (2016), MZDF: An Energy Aware Framework for Multi-Zone Data Fusion Technique in WSN, International Journal of Applied Engineering Research, 11(4), pp 2263-2270.
  31. Vesanto J, Alhoniemi E (2000), Clustering of Self Organizing Map. In: IEEE Transactions on Neural Networks, Vol. 11, No. 3, 2000, pp. 586-600.
  32. Dehni L, Kief F, Bennani Y (2005), Power Control and Clustering in Wireless Sensor Networks. In: Proceedings of Med-Hoc-Net: Mediterranean Ad Hoc Networking Workshop, France
  33. Dehni L, Krief F, Bennani Y (2005). Power Control and Clustering in Wireless Sensor Networks. In: Challenges in Ad Hoc Networking, vol , p.31-4
  34. Smith, D., Singh, S. (2006) “Approaches to Multisensor Data Fusion in Target Tracking: A Survey”, IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, Vol. 18, No. 12, pp.
  35. Heinzelman W, Chandrakasan A, Balakrishnan H. (2000), Energy-Efficient Communication Protocol for Wireless Microsensor Networks. In: Proc. 33rd Hawaii Int’l. Conf.Sys. Sc.
  36. Saber AMRI and Med Lassaad KADDACHI. (2014), SOM based energy efficient multi hop hierarchical routing protocol for wsn, NNGT Int. J. of Artifical Intellegent, vol. 1, July 2014.
Index Terms

Computer Science
Information Sciences

Keywords

WSN ANN SOM DF Decision Energy.

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