In this paper, the authors adopt a neural approach to deal with the problem of routing in a packet switching network. The aim is to define a routing strategy which will combine the advantages of both the centralized and the distributed approaches. The neural approach presented is based on the idea of inserting a neural network (N/N) into each node in the computer network which will be responsible for computing the route between its node and the immediately adjacent one. Two distributed routing solutions are presented in the paper based on an optimizing network and a mapping network. The routing obtainable and the implementation resources needed for the two approaches are evaluated. Finally, the performance offered by the neural strategies proposed is compared with that offered by classical distributed and centralized routing solutions. As a parameter of merit, the effect of overloading caused by the additional traffic present in each solution is used.
Technology Using Neural Network Optimization Path in Packet Switching Network
