A neural network approach to routing in multihop radio networks

The problem of routing is addressed for the minimization of congestion as a first step toward the solution of the joint routing-scheduling problem in packet radio networks. This is formulated as a combinatorial-optimization problem, and a Hopfield neural network model is developed for its solution. The method of Lagrange multipliers is used, which permits these coefficients to vary dynamically along with the evolution of the system state. Extensive software simulation results demonstrate the ability of this approach to determine good sets of routes in large, heavily-congested networks