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The ant colony optimization algorithm is used to find the optimal path based on the behavior of an ant while searching a food. It will communicate with other ants using the pheromone to find the best solution. In this paper, we introduce recursive ant colony optimization (RACO) in the wireless mesh network. This technique is used to subdivide a large network into smaller networks and based on the network, the shortest path is found in each subproblem, and finally it is combined to generate an optimal path for the network. In each subproblem, the iteration is performed recursively to obtain the shortest path in that subproblem. In our paper, we use recursive ant colony to reduce redundancy in connection and so the data will transfer in less time effectively. RACO is used to find best solutions more accurate than the other ant colony systems. Isolation of a subproblem is reduced in RACO.

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