Neural network implementation of the shortest path algorithm for traffic routing in communication networks

A neural network computation algorithm is introduced to solve for the optimal traffic routing in a general N-node communication network. The algorithm chooses multilink paths for node-to-node traffic which minimize a certain cost function. Unlike the algorithm introduced earlier in this area, knowledge of the number of links between each origin-destination pair is not required by the algorithm, therefore it can be applied to variable-length path routing problems. The neural network structure for implementing the algorithm is a modified form of the one used by the traveling salesman algorithm. Computer simulation in a nine- and sixteen-node grid network showed that the algorithm performs extremely well in single and multiple paths