CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Classification of Swarm Intelligence based Clustering Methods

by Pooja Nagchoudhury, Kavita Choudhary
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 91 - Number 6
Year of Publication: 2014
Authors: Pooja Nagchoudhury, Kavita Choudhary
10.5120/15887-5078

Pooja Nagchoudhury, Kavita Choudhary . Classification of Swarm Intelligence based Clustering Methods. International Journal of Computer Applications. 91, 6 ( April 2014), 28-33. DOI=10.5120/15887-5078

@article{ 10.5120/15887-5078,
author = { Pooja Nagchoudhury, Kavita Choudhary },
title = { Classification of Swarm Intelligence based Clustering Methods },
journal = { International Journal of Computer Applications },
issue_date = { April 2014 },
volume = { 91 },
number = { 6 },
month = { April },
year = { 2014 },
issn = { 0975-8887 },
pages = { 28-33 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume91/number6/15887-5078/ },
doi = { 10.5120/15887-5078 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:12:04.918358+05:30
%A Pooja Nagchoudhury
%A Kavita Choudhary
%T Classification of Swarm Intelligence based Clustering Methods
%J International Journal of Computer Applications
%@ 0975-8887
%V 91
%N 6
%P 28-33
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The nodes in wireless sensor networks (WSN) need to be deployed optimally to cover whole geographic area and the communication link between them should be optimal. During deployment the proper strategy is required to optimally deploy the sensor nodes in the area. The sensor nodes can be compared with swarms which are homogenous agents. Swarm intelligence methods have been applied over the clustering of nodes in WSN and some of the approached have shown significant improvements in comparison with the non-swarm intelligence based algorithms. In this paper, we have tried to review latest techniques to create clusters using nature inspired methods. Proper classification with discussion of merits and demerits has been done. Scope of work in this area has been searched and inferred as conclusion. After the optimal deployment the next phase of needed is the energy efficient multi-hop routing among the nodes for communication of the packets to the base station. This multi-hop routing requires the optimal cluster head selection and maximum time of death of complete circuit achievable to get an optimally clustered network.

References
  1. S. Indu, M. Shubham, C. Santanu, and B. Asok, "Bio-Inspired Distributed Sensing Using a Self-Organizing Sensor Network", Journal of Engineering, Vol. 2013, Article ID 959430, 16 pages, 2013.
  2. S. Sribala,"Energy Efficient Routing in Wireless Sensor Networks Using Modified Bacterial Foraging Algorithm", IJREAT International Journal of Research in engineering and Advanced Technology, Vol. 1, Issue 1, March 2013, ISSN: 2320-8791
  3. Aruna, G. Vikas, "Soft Computing Implementation for Mobile Ad-hoc Network Optimization Using Bacteria Foraging Optimization Algorithm", International Journal of Computer Science and Communication Engineering, Vol. 2, Issue 2, May 2013, ISSN 2319-7080.
  4. S. Anikit, T. Jawahar, "An Energy Efficient Network Life Time Enhancement Proposed Clustering Algorithm for Wireless Sensor Networks", International Journal of Enhanced Reacherch in Management and Computer Application, Vol. 2,Issue 7, July 2013,ISSN: 2319-7471, pp. 1-4.
  5. M. V. Ramesh, P. L. Divya, P. Rekha, R. V. Kulkarni, "Performance Enhancement in Distributed Sensor Localization Using Swarm Intelligence", Advances in Mobile Network, Communication and its Applications (MNCAPPS), 2012 International Conference on , vol. , no. , 1-2 Aug. 2012, pp. 103-106.
  6. K. Anil, K. Arun, S. S. Jasbir, S. Satvir, "Computational Intelligence based algorithm for node localization in Wireless Sensor Networks", 6th IEEE International Conference Intelligent Systems (IS), Sofia, 6-8 Sept. 2012, pp. 431 - 438.
  7. P. T. V. Bhuvaneswari, S. Karthikeyan, B. Jeeva, M. A. Prasath, "An Efficient Mobility Based Localization in Underwater Sensor Networks", Computational Intelligence and Communication Networks (CICN), 2012 Fourth International Conference on , vol. , no. , 3-5 Nov. 2012, pp. 90-94.
  8. V. K. Raghavendra, K. V. Ganesh, "Particle Swarm Optimization in Wireless-Sensor Networks: A Brief Survey", Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on, Vol. 41, no. 2, March 2011, pp. 262-267.
  9. K. C. Navroop, "Energy Balancing Intelligent Clustering Protocol for Wireless Sensor Network", Journal of Global Research in Computer Science, Vol. 2, no. 7, July 2011, ISSN-2229-371X.
  10. P. M. Jalil, M. G. Rama, B. G. Praveen, A. Ehsan, "Total GPS-free Localization Protocol for Vehicular Ad Hoc and Sensor Networks (VASNET)", Computational Intelligence, Modelling and Simulation (CIMSiM), 2011 Third International Conference on , vol. , no. , 20-22 Sept. 2011, pp. 388-393.
  11. W. Chunjuan, Y. Junjie, G. Yanjie, Z. Zhimei, "Cluster-based routing protocols in wireless sensor networks: A survey", Computer Science and Network Technology (ICCSNT), 2011 International Conference on, vol. 3, no. , 24-26 Dec. 2011, pp. 1659-1663.
  12. S. G. Gurjot, S. Kanwaljit, S. D Balwinder, "Sensor node deployment using Bacterial Foraging Optimization", Recent Trends in Information Systems (ReTIS), 2011 International Conference on, vol. , no. , 21-23 Dec. 2011, pp. 73-76.
  13. L. Qiao, C. Lingguo, Z. Baihai, F. Zhun, "A low energy intelligent clustering protocol for wireless sensor networks", Industrial Technology (ICIT), 2010 IEEE International Conference on , vol. , no. , 14-17 March 2010, pp. 1675-1682.
  14. C. Charalambos, C. Shuguang, "A biologically inspired networking model for wireless sensor networks", Network, IEEE, vol. 24, no. 3, May-June 2010, pp. 6-13.
  15. Y. Gao, Y. Zhuang, T. Ni, K. Yin, T. Xue, "An improved genetic algorithm for wireless sensor networks localization", Bio-Inspired Computing: Theories and Applications (BIC-TA), 2010 IEEE Fifth International Conference on , vol. , no. , 23-26 Sept. 2010, pp. 439-443.
  16. V. K. Raghavendra, K. V. Ganesh, "Bio-inspired Algorithms for Autonomous Deployment and Localization of Sensor Nodes", Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on, vol. 40, no. 6, Nov. 2010, pp. 663-675.
  17. Y. Li-ying, Z. Jun-ying, W. Wen-jun, "Cluster Ensemble Based on Particle Swarm Optimization", Intelligent Systems, 2009. GCIS '09. WRI Global Congress on , vol. 3, no. , 19-21 May 2009, pp. 519-523.
  18. Z. S. Saleh, E. Vinayak, C. Wei, M. Richard, "Localization strategies for large-scale airborne deployed wireless sensors", Computational intelligence in miulti-criteria decision-making, 2009. mcdm '09. ieee symposium on , vol. , no. , March 30 2009-April 2 2009, pp. 9-15.
  19. V. K. Raghavendra, K. V. Ganesh, X. C. Maggie, "Bio-inspired node localization in wireless sensor networks", Systems, Man and Cybernetics, 2009. SMC 2009. IEEE International Conference on, vol. , no. , 11-14 Oct. 2009, pp. 205-210.
  20. Z. Bojkovic and B. Bakmaz, "A survey on wireless sensor networks deployment", WSEAS Trans. Commun. , vol. 7, no. 12, 2008, pp. 1172–1181.
  21. N. M. A. Latiff, C. C. Tsimenidis, and B. S. Sharif, "Performance comparison of optimization algorithms for clustering in wireless sensor networks", in Proc. IEEE Int. Conf. Mobile Ad Hoc Sens. Syst. , Oct. 8–11, 2007, pp. 1–4.
  22. G. Mao, B. Fidan, and B. D. O. Anderson, "Wireless sensor network localization techniques", Comput. Netw. , vol. 51, no. 10, 2007, pp. 2529–2553.
  23. N. M. A. Latiff, C. C. Tsimenidis, and B. S. Sharif, "Energy-aware clustering for wireless sensor networks using particle swarm optimization", in Proc. 18th IEEE Int. Symp. Pers. , Indoor Mobile Radio Commun. , 2007, pp. 1–5.
  24. O. Younis, M. Krunz; S. Ramasubramanian, "Node clustering in wireless sensor networks: recent developments and deployment challenges", Network, IEEE, vol. 20, no. 3, May-June 2006, pp. 20-25.
  25. C. Zhuo, M. Qing-Chun, "An incremental clustering algorithm based on swarm intelligence theory", Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on , Vol. 3, no. , 26-29 Aug. 2004, pp. 1768-1772.
  26. J. N. Al-Karaki, A. E. Kamal, "Routing techniques in wireless sensor networks: a survey", Wireless Communications, IEEE, Vol. 11, no. 6, Dec. 2004, pp. 6-28.
  27. B. Wu, Z. Shi, "A clustering algorithm based on swarm intelligence", Info-tech and Info-net, 2001. Proceedings. ICII 2001 - Beijing. 2001 International Conferences on , vol. 3, no. , vol. 3, 2001, pp. 58-66.
  28. S. Kazem, M. Daniel, Z. Taieb, "Wireless Sensor Networks Technology, Protocols and Applications", A John Wiley and Sons, INC. , Publication, 2007, ISBN 978-0-471-74300-
Index Terms

Computer Science
Information Sciences

Keywords

Wireless sensor networks (WSN) Swarm Intelligence Clustering Bacterial Foraging Optimization (BFO) Algorithms and Enhanced BFO.

Powered by PhDFocusTM