Call for Paper - January 2023 Edition
IJCA solicits original research papers for the January 2023 Edition. Last date of manuscript submission is December 20, 2022. Read More

Optimal Route Search in Mobile Ad-Hoc Network using Ant Colony Optimization

Print
PDF
International Journal of Computer Applications
© 2012 by IJCA Journal
Volume 50 - Number 2
Year of Publication: 2012
Authors:
Bandana Mahapatra
10.5120/7747-0800

Bandana Mahapatra. Article: Optimal Route Search in Mobile Ad-Hoc Network using Ant Colony Optimization. International Journal of Computer Applications 50(2):47-51, July 2012. Full text available. BibTeX

@article{key:article,
	author = {Bandana Mahapatra},
	title = {Article: Optimal Route Search in Mobile Ad-Hoc Network using Ant Colony Optimization},
	journal = {International Journal of Computer Applications},
	year = {2012},
	volume = {50},
	number = {2},
	pages = {47-51},
	month = {July},
	note = {Full text available}
}

Abstract

In Ad-Hoc networks the mobile nodes communicate with each other using multi-hop wireless links. The main drawback of such network is that there are no stationary infrastructures to route the packets. Hence, routing protocols have to adapt quickly and elegantly to frequent and unpredictable changes in network technology and they have to do so while conserving the memory, power and bandwidth resource. The Ant Colony Optimization technique implemented upon such networks have helped the nodes in finding the routes to different nodes in an optimized way same as ants find the optimum route to its food. The techniques provided so far have considered the search space utilized by a node as the space occupied by all the nodes that are present in the network which requires message passing among all the nodes that are present in the network consuming plenty of bandwidth and power only to find the routes to different nodes. If we divide the search space among the nodes forming clusters then the number of messages communicating will be reduced thereby reducing the bandwidth occupied and power consumed.

References

  • Jan Komorowski, Zdzislaw Pawlak, L. P. A. S. Rough sets: a tutorial, 1998.
  • Pawlak, Z. Rough sets: Theoretical aspects of reasoning about data. Kluwer Dordrecht,1991. [
  • Adrzej Skowron, J. S. Tolerance approximation spaces. Fundamental Informaticae 27, 2-3 (1996), 245 -253.
  • Saori Kawasaki, Ngoc Binh Nguyen, T. B. H. Hierarchical document clustering based on tolerance rough set model. In Principles of Data Mining and Knowledge Discovery, 4th European Conference, PKDD 2000, Lyon, France, September 13-16, 2000,Proceedings (2000), D. A. Zighed, H. J. Komorowski, and J. M. Zytkow, Eds. , vol. 1910 of Lecture Notes in Computer Science, Springer.
  • Tu Bao Ho, N. B. N. Nonhierarchical document clustering based on a tolerance rough set model. International Journal of Intelligent Systems 17, 2 (2002),199{212.
  • Jiawei Han, M. K. Data Mining: Concepts and Techniques, 1st ed. Morgan Kaufmann,2000.
  • Porter, M. F. An algorithm for su±x stripping. In Readings in Information Retrieval, P. W. Karen Sparck Jones, Ed. Morgan Kaufmann, San Francisco, 1997, pp. 130{137.
  • Weiss, D. A clustering interface for web search results in polish and english, 2001.
  • Osinski, S. An algorithm for clustering of web search result. Master's thesis, Poznan University of Technology, Poland, June 2003.
  • Zamir, O. , and Etzioni, O. Grouper: a dynamic clustering interface to web search results. Computer Networks (Amsterdam, Netherlands: 1999) 31, 11-16 (1999), 1361-1374.
  • Smadja, F. A. From n-grams to collocations: An evaluation of xtract. In 29th Annual Meeting of the Association for omputational Linguistics, 18-21 June 1991, University of California, Berkeley, California, USA, Proceedings (1991), pp. 279-284.
  • Infoseek. http://infoseek. com.