Abstract
Intelligence, a mutant of biological swarms, exhibits numerous powerful features which are described in communication networks. With the increase in size and complexity of network, performance analysis is becoming difficult. With scalability of network, it becomes difficult to manage the route and indicate which one is the best. The intent of this paper is to find optimal path for routing of calls in a telecommunication network and achieve Load Sharing. For finding optimal path, the pheromone laying and sensing property of natural swarms is used. In this research work we present a simulated network model that uses artificial ants and simulated pheromone for finding optimal path from source to destination. Next node selection is done on the basis of local pheromone distribution and pheromone updation takes place based on the congestion encountered on the node. Simulation results using ACO mode will be compared with non-ACO mode using graphs.
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