Enhanced Ant Colony Based Algorithm for Routing in Mobile Ad Hoc Network
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Enhanced Ant Colony Based Algorithm for Routing in Mobile Ad Hoc Network

Authors: Cauvery N. K., K. V. Viswanatha

Abstract:

Mobile Ad hoc network consists of a set of mobile nodes. It is a dynamic network which does not have fixed topology. This network does not have any infrastructure or central administration, hence it is called infrastructure-less network. The change in topology makes the route from source to destination as dynamic fixed and changes with respect to time. The nature of network requires the algorithm to perform route discovery, maintain route and detect failure along the path between two nodes [1]. This paper presents the enhancements of ARA [2] to improve the performance of routing algorithm. ARA [2] finds route between nodes in mobile ad-hoc network. The algorithm is on-demand source initiated routing algorithm. This is based on the principles of swarm intelligence. The algorithm is adaptive, scalable and favors load balancing. The improvements suggested in this paper are handling of loss ants and resource reservation.

Keywords: Ad hoc networks, On-demand routing, Swarmintelligence.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1056140

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[1] Andrew S Tannenbaum, "Computer Networks", 4th Edition, Prentice- Hall of India.
[2] Cauvery N K, Dr K V Viswanatha, "Ant Algorithm for Mobile Ad Hoc network" Proceedings of the International Conference on Advanced Computing and Communication Technologies for High Performance Applications,2008.
[3] Schoonderwoerd R, Holland O, Bruten J, Rothkrantz L. "Ant-Based load Balancing in telecommunications networks, Adaptive Behavior Hewlelt- Packard Laboratories, Bristol-England, pp 162-207, 1996.
[4] Di Caro, G., Dorigo, M, "Antnet: Distributed stigmergetic control communications networks. Journal of Artificial Intelligence Research pp 317-365, 1998.
[5] Schoonderwoerd R , Holland O Bruten J, "Ant like agents for load balancing in Telecommunication Networks", Hewlelt-Packard Laboratories, Bristol-England, 1997
[6] Di Caro and Marco Dorigo, "Mobile Agents for adaptive Routing", Gianni, http://www.cs.berkeley.edu/~culler/cs294-s00/antnet.ps
[7] Dorigo M, Di Caro G, "A mobie agents approach to Adaptive Routing Technical report", IRIDA-Free Brussels University, Belgium, 1997
[8] Dorigo M & Gambardella L, "Ant colony system: A Cooperative learning approach to the traveling salesman problem", IEEE Transaction on Evolutionary Computation, Vol. 1, N1, pp53-66
[9] Liang S, Zincir Heywood A N, Heywood M I, "The effect of Routing under local information using a Social insect Metaphor", IEEE International Congress of Evolutionary Computation, pp 1438-1443, May 2002.
[10] M. Heissenbilttel, T. Braun, "Ants-Based Routing in Large Scale Mobile Ad-Hoc Networks", http://www.iam.unibe.ch/~heissen/Papers/KIVS03_Final.pdf
[11] Nader F Mir, "Computer and communication Networks", Pearson Education, 2007
[12] Mesut Gunes,Udo Sorges, Imed Bouazizi, "ARA-The Ant-Colony Based Routing Algorithm for MANETs" International workshop on Ad Hoc Networking (WAHN 2002) couver, British Columbia, Canada, August 18-21,2002 http://www.lix.polytechnique.fr/~tomc/P2P/Papers/Theory/Ants.pdf