creating dynamic sub-route to control congestion based on learning automata technique in mobile ad hoc networks

ad hoc mobile networks have dynamic topology with no central management. because of the high mobility of nodes, the network topology may change constantly, so creating a routing with high reliability is one of the major challenges of these networks .in the proposed framework first, by finding directions to the destination and calculating the value of the rout the combination of this value with the average total probability of nodes for each route is considered to be a final value and by choosing a route among all routes leading to destination, routing operation is performed randomly and desirability or undesirability of the rout will be examined based on learning automata technique to select the optimal route for the next times. the proposed method attempts to encompass all parameters to control congestion on the network accurately and efficiently. to evaluate the proposed method, the results were compared with previous related works and compared with other methods which indicated that the proposed method has a better performance.