CFP last date
20 December 2024
Reseach Article

Survey on Optimization Techniques of RFID for Internet of Things

by Komal Singh, Arun Aggarwal
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 148 - Number 9
Year of Publication: 2016
Authors: Komal Singh, Arun Aggarwal
10.5120/ijca2016911260

Komal Singh, Arun Aggarwal . Survey on Optimization Techniques of RFID for Internet of Things. International Journal of Computer Applications. 148, 9 ( Aug 2016), 1-5. DOI=10.5120/ijca2016911260

@article{ 10.5120/ijca2016911260,
author = { Komal Singh, Arun Aggarwal },
title = { Survey on Optimization Techniques of RFID for Internet of Things },
journal = { International Journal of Computer Applications },
issue_date = { Aug 2016 },
volume = { 148 },
number = { 9 },
month = { Aug },
year = { 2016 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume148/number9/25782-2016911260/ },
doi = { 10.5120/ijca2016911260 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:52:51.711710+05:30
%A Komal Singh
%A Arun Aggarwal
%T Survey on Optimization Techniques of RFID for Internet of Things
%J International Journal of Computer Applications
%@ 0975-8887
%V 148
%N 9
%P 1-5
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

RFID is a radio frequency identification technology using radio waves to transfer the data between a reader and a tag. RFID allows the sensor to read from a distance without sight contact, a unique code associated with tags. Data stored on a tag is transferred through radio frequency linked by RFID tagging which is a form of automatic identification and data capture technology. RFID is used in wide range of area such as Supply chain management factory automation, traffic monitoring, real time monitoring of health, access control, warehouses, people tracking. RFID is a technology that has the possibility to make great economic impacts on many industries. In this paper, we proposed optimization techniques for RFID in internet of things. Optimization for an RFID reader is a technique to reduce the cost of hardware. There are several techniques which have been proposed like Ant colony optimization, Differential evolution, Particle swarm optimization, Genetic algorithm. In this paper, it will demonstrate and compare all the techniques and give more effectively and efficiently approaches that increase in network system of internet of things.

References
  1. R. Want, “An introduction to RFID technology,” IEEE Pervasive Computing, pp. 25-33, 2006.
  2. R.H. Weber, Accountability in the Internet of Things. Computer La w & Security Review, 27(2), p133-138, 2011. http://dx.doi.org/10.1016/j.clsr.2011.01.005.
  3. Marcus Randall, Andrew Lewis, Amir Galehdar, David Thiel. Using Ant Colony Optimization to Improve the Efficiency of Small Meander Line RF-IDAntennas.// In 3rd IEEE International e-Science and Grid Computing Conference, 2007. http://www98.griffith.edu.au/dspace/bitstream/1007 2/17063/1/47523_1.pdf.
  4. Po-Jen Chuang and Wei-Ting Tsai Department of Electrical Engineering Tamkang University Tamsui, New Taipei City Taiwan 25137, R. O. C. . J. Cho, Y. Shim, T. Kwon, Y.Choi,S.Pack,and. Kim, “SARIF:
  5. A novel framework for integrating wireless sensor and RFID networks,”IEEE Wireless Commun., vol. 14, no. 6,pp. 50–56, June 2009.
  6. T. Yashiro, S. Kobayashi, N. Koshizuka, and K. Sakamura, “An Internet of Things (IoT) Architecture for Embedded Appliances”, Proceedings of the 2013 IEEE Region 10 Humanitarian Technology Conference, (2013), pp. 314- 319. . T. J. Green, V. Tannen . Models for incomplete and probabilistic Information. IEEE Data Engineering Bulletin , 29(1), pp. 17–24, March 2006.
  7. Gong, Y., M.Shen, J. Zhang, 2011. “Optimizing RFID Network Planning by Using a Particle Swarm Optimization Algorithm with Redundant Reader Elimination.” IEEE Transactions On Industrial Informatics, 1-13.
  8. Giampaolo, E., F. Fornì, G. Marrocco, 2010. “RFID-Network Planning by Particle SwarmOptimization.” Antennas and Propagation EuCAP Proceedings of the Fourth European Conference.
  9. R. Poli ”Analysis of the publications on the applications of particle swarm optimization” Journal of Artificial Evolution and applications, Article ID 685175, 10 pages, 2008.
  10. ISO/ IEC JTC1 SC31 WG4 SG3 18000-6 Proposal, 2002: Information Technology AIDC .Techniques- RFID for Item Management - Air Interface, Part 6 -Parameters for Air Interface Communications at UHF.
  11. E. Mezura-Montes, J. Vel_ azquez- Reyes, and C. A. Coello Coello. A comparative study of differential evolution Variants for global optimization. In Genetic and Evolutionary Computation Conference(GECCO'06), pages 485{492, Seattle, Washington,USA, 2006.
  12. J. Montgomery. Crossover and the different faces of Differential evolution searches. In IEEE CEC 2010, Barcelona, Spain, 2010. IEEE.
  13. G. C. Onwubolu and D. Davendra, editors. Differential Evolution: A Handbook for Global Permutation-Based Combinatorial Optimization, volume 175 of Studies in Computational Intelligence. Springer, 2009.
  14. M. Randall, A. Lewis, A. Galehdar, and D. Thiel. Using ant colony optimization to improve the efficiency of small meander line RFID antennas. In Proceedings of the 3rd IEEE International e-Science and Grid Computing Conference, 2007. .
  15. G. Pampara, A. P. Engelbrecht, and N. Franken, “Binary Differential evolution,” in Proc. IEEE Congr. Evol. Comput., Jul. 2006, pp. 1873–1879.
  16. K. Deb. Multi-Objective Optimization using Evolutionary Algorithms. Wiley, 2002
  17. Y. Watanabe, K. Watanabe, and H. Igarashi, “Optimization of meander line antenna considering coupling between nonlinear circuit and electromagnetic waves for UHF-band RFID,” IEEE Trans. Magn., vol.47, no. 5, pp. 1506-1509, 2011.
  18. J.M. Johnson and Y. Rahmat-Samii, “Genetic algorithms in Engineering electromagnetic ,” IEEE Antennas Propagate . Mag., vol. 39, pp. 7-25, Aug. 1997.
  19. Y. Rahmat-Samii, E. Michielssen, Electromagnetic Optimization by Genetic Algorithms. New York: John Wiley and Sons, Inc., 1999..
  20. D. Karaboga and B. Basturk, “Artificial bee colony (ABC) optimization algorithm for solving constrained optimizationproblems,” in Foundations of Fuzzy Logic and Soft Computing, vol. 4529 of Lecture Notes in Computer Science, pp. 789–798,Springer, Berlin, Germany, 2007.
  21. R. Storn and K. Price. Differential evolution { a simple and efficient heuristic for global optimization over continuous spaces. J. Global Optimization., 11:341{359, 1997.
  22. D. Karaboga and B. Akay, “A comparative study of artificial Bee colony algorithm,” Applied Mathematics and Computation, vol.214, no. 1, pp. 108–132, 2009.
  23. John A. Stankovic, “Wireless Sensor Networks”, 2006
Index Terms

Computer Science
Information Sciences

Keywords

RFID Optimization techniques IOT.