We propose a dynamic programming for optimal packet routing control using two neural networks within the framework of statistical physics. An energy function for each neural network is defined in order to express competition between a queue length and the shortest path of a packet to its...

We investigate a packet flow problem in a computer network within a framework of statistical physics. We propose a model for packet routing control by putting a neural network at each node. The energy function for the whole system is defined in order to express competition among queue length,...

We investigate an optimal network structure for packet flow on large-scale networks. For this aim, we introduce a cost function which represents efficiency of the packet flow. Our strategy for obtaining an optimal network is to reconnect links in the network so as to minimize the defined cost...