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Reseach Article

Location Estimation in Wireless Sensor Network using H-PSO Algorithm

Published on July 2015 by Sivakumar.s, Gavya.p.v
International Conference on Innovations in Computing Techniques (ICICT 2015)
Foundation of Computer Science USA
ICICT2015 - Number 2
July 2015
Authors: Sivakumar.s, Gavya.p.v
2ee9b15b-aefb-4c04-b5c1-5df5488c8875

Sivakumar.s, Gavya.p.v . Location Estimation in Wireless Sensor Network using H-PSO Algorithm. International Conference on Innovations in Computing Techniques (ICICT 2015). ICICT2015, 2 (July 2015), 27-32.

@article{
author = { Sivakumar.s, Gavya.p.v },
title = { Location Estimation in Wireless Sensor Network using H-PSO Algorithm },
journal = { International Conference on Innovations in Computing Techniques (ICICT 2015) },
issue_date = { July 2015 },
volume = { ICICT2015 },
number = { 2 },
month = { July },
year = { 2015 },
issn = 0975-8887,
pages = { 27-32 },
numpages = 6,
url = { /proceedings/icict2015/number2/21465-1483/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Innovations in Computing Techniques (ICICT 2015)
%A Sivakumar.s
%A Gavya.p.v
%T Location Estimation in Wireless Sensor Network using H-PSO Algorithm
%J International Conference on Innovations in Computing Techniques (ICICT 2015)
%@ 0975-8887
%V ICICT2015
%N 2
%P 27-32
%D 2015
%I International Journal of Computer Applications
Abstract

Localization has become one of the mandatory services in wireless sensor networks (WSNs) while dealing with critical operations such as coverage, deployment, routing, target tracking and rescue operations. Since the necessity of WSN has increased drastically to provide best solution with accurate results of sensor nodes, it mainly depends on the WSN node localization. This paper initially describes on Mobile Anchor Positioning - Mobile Anchor & Neighbour (MAP - M&N), a range-free localization method, which makes use of the beacon packets of mobile anchor and the location packets of neighboring nodes to estimate the position of nodes and to improve the localization accuracy. The anchor node, which is equipped with global positioning system (GPS), broadcasts its coordinates to the sensor nodes as it moves through the network. The result of MAP-M&N method serves as input to Heuristic Particle Swarm Optimization (H-PSO) algorithm. By using H-PSO algorithm, it can be observed that localization accuracy of the sensor nodes seems to improve significantly than by using only MAP-M&N method for location estimation.

References
  1. I. F. Akyildiz,W. Su,Y. Sankarasubramaniam, E. Cayirci, "Wireless Sensor Networks: a Survey", IEEE Communication. Mag. , 2002, Vol. 40, No. 8, pp. 102 –114.
  2. Guibin Zhu, Qiuhua Li, Peng Quan, Jiuzhi Ye , "A GPS-free Localization Scheme for Wireless Sensor Networks", 12th IEEE International Conference on Communication Technology (ICCT 2010), Nov 2010, pp. 401-404.
  3. Guoqiang Mao, Bar?s¸ Fidan , and Brian D. O. Anderson, "Wireless Sensor Networks Localization Techniques ," Science Direct, Computer Networks 51, 2007, pp. 2599-2533.
  4. Anil Kumar, Arun Khoslay, Jasbir Singh Saini, Satvir Singh, "Meta-Heuristic Range Based Node Localization Algorithm for Wireless Sensor Networks", 2012.
  5. Han Bao, Baoxian Zhang, Cheng Li, and Zheng Yao, "Mobile Anchor Assisted Particle Swarm Optimization (PSO) based localization algorithms for Wireless Sensor Networks," Wireless Communications and Mobile Computing, Oct. 2012, Vol. 12, Iss. 15, pp. 1313-1325.
  6. Nabil Ali Alrajeh, Maryam Bashir and Bilal Shams, "Localization techniques in wireless sensor networks", International Journal of Distributed sensor networks, 2013.
  7. Love preet Singh, Sukhpreet kaur, " Techniques of node localization in wireless sensor networks: Review", International Journal of innovative Research in Computer and Communication Engineering,Vol. 2,Issue 5,May 2015
  8. Hoang Q. T. , Le T. N. , and Yoan Shin, "An RSS comparison based Localization in Wireless Sensor Networks," 8th workshop on Positioning Navigation and communication (WPNC 2011), April 2011, pp. 116-121.
  9. Guowei Shen, Zetik R, Honghui Yan, Hirsch O. , and Thoma, R. S. ," Time of Arrival Estimation for range-based localization in UWB sensor networks", in Proc. of IEEE Int. Conf. on Ultra-Wideband (ICUWB 2010),Sept. 2010,Vol. 2,pp. 1-4.
  10. Pengfei Peng, Hao Luo, Zhong Liu, Xiongwei Ren " A cooperative target location algorithm based on time difference of arrival in wireless sensor networks", International Conference on Mechatronics and Automation (ICMA 2009), Aug. 2009, pp. 696-701
  11. Yanping Zhu, Daqing Huang, and Aimin Jiang, "Network Localization using Angle of Arrival," IEEE International Conference on Electro/Information Technology (EIT 2008), May 2008, pp. 205-210.
  12. Binwei Deng, Guangming Huang, Lei Zhang, and Hao Liu, "Improved Centroid Localization Algorithms in WSNs," 3rd International Conference on Intelligent System and Knowledge Engineering (ISKE 2008), Nov 2008, Vol. 1, pp. 1260-1264.
  13. Zhang Zhao-yang, Gou Xu, Li and Shan-shan Huang, "DV Hop based Self-Adaptive Positioning in Wireless Sensor Networks," 5th International Conference on Wireless Communications, Networking and Mobile Computing (WiCom 2009), Sept. 2009, pp. 1-4
  14. Kuo-Feng Ssu, Ou, C. -H. , Jiau, H. C. : 'Localization with mobile anchor points in wireless sensor networks', IEEE Transactions on Vehicular Technol, May 2005, Vol. 54, Iss. 3, pp. 1187–1197.
  15. W-H Liao, Y. C. Lee, and S. P. Kedia, "Mobile Anchor Positioning of Wireless Sensor Networks," IET communications, 2011, Vol. 5, Issue 7, pp. 914-921.
  16. Chi-Chang Chen, Yon Nong Li, Chi Yu Chang, "A novel range-free localization scheme for wireless sensor networks", International journal on applications of graph theory in wireless ad hoc networks and sensor networks (GRAPH-HOC), September 2012, Vol. 4, No. 2, pp. 1-13.
Index Terms

Computer Science
Information Sciences

Keywords

Localization Wireless Sensor Networks Mobile Anchor Gps Heuristic Particle Swarm Optimization Algorithm.