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An Efficient Multiple Ant Colony Based Routing Protocol to Support Multimedia Communication in Ad Hoc Wireless Network


Affiliations
1 Departmaent of Computer Science in Sri Parasakthi College for Women, India
2 School of Computer Science and Head of the Department of Computer Science and Engineering, Alagappa University, India
     

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The major problem in Ad hoc Networks is to find a route between the communication end points. The topology of the network changes constantly due to the mobility of the nodes and paths which were initially competent and can quickly become incompetent or even infeasible. Ant Colony Optimization (ACO) is a biological inspiration simulating the ability of real ant colony of finding the shortest path between the nest and food source. Ant colony algorithms are motivated by the observation of real ant colonies. ACO is one of the successful applications of Swarm Intelligence (SI) which is the field of Artificial Intelligence (AI) that studies the intelligent behavior of ants. In this paper, Multiple Ant Colony Optimization based routing protocol is used to support multimedia communication in Ad Hoc Network. This approach avoids the stagnation problem on ants. This approach increases effectiveness and adaptiveness. Moreover, tabu search is used in this approach which avoids the blind alley problem of ants.

 


Keywords

Swarm Intelligence (SI), Ant Colony Optimization (ACO), Stagnation, Tabu Search.
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  • An Efficient Multiple Ant Colony Based Routing Protocol to Support Multimedia Communication in Ad Hoc Wireless Network

Abstract Views: 215  |  PDF Views: 3

Authors

M. Sivajothi
Departmaent of Computer Science in Sri Parasakthi College for Women, India
E. R. Naganathan
School of Computer Science and Head of the Department of Computer Science and Engineering, Alagappa University, India

Abstract


The major problem in Ad hoc Networks is to find a route between the communication end points. The topology of the network changes constantly due to the mobility of the nodes and paths which were initially competent and can quickly become incompetent or even infeasible. Ant Colony Optimization (ACO) is a biological inspiration simulating the ability of real ant colony of finding the shortest path between the nest and food source. Ant colony algorithms are motivated by the observation of real ant colonies. ACO is one of the successful applications of Swarm Intelligence (SI) which is the field of Artificial Intelligence (AI) that studies the intelligent behavior of ants. In this paper, Multiple Ant Colony Optimization based routing protocol is used to support multimedia communication in Ad Hoc Network. This approach avoids the stagnation problem on ants. This approach increases effectiveness and adaptiveness. Moreover, tabu search is used in this approach which avoids the blind alley problem of ants.

 


Keywords


Swarm Intelligence (SI), Ant Colony Optimization (ACO), Stagnation, Tabu Search.