A NEURAL-NETWORK APPROACH TO SOLVING THE LINK ACTIVATION PROBLEM IN MULTIHOP RADIO NETWORKS

We address the problem of ''link activation'' or ''scheduling'' in multihop packet radio networks. The objective is to determine a conflict-free schedule of minimum length that satisfies the specified end-to-end communication requirements. It is well known that this problem, in almost all of its forms, is a combinatorial-optimization problem of high complexity. We approach this problem by the use of a Hopfield neural network model in which the method of Lagrange multipliers is used to vary dynamically the values of the coefficients used in the connection weights.