AN ADAPTWE SHORTEST-PATH ON-LINE ROUTING ALGORITHM
Ura Cnrs · 1998
In this paper, we describe a new adaptive routing algorithm for meshed-topology deflection networks. Our algorithm is based on a local learning method which evolves in order to produce a local spatial representation of the trac. We prove that we can set the parameters of the learning algorithm such that our adaptive policy is a shortest path routing. Then we show experimentally the efficiency of our algorithm. First, we compare the routing policies in a grid network, under an uniform load. Second, we create local congestion in order to show that the adaptive routing scheme avoid the overloaded region. Moreover, we propose a more realistic trac model, and show that our algorithm is valid, even in such context. These results show the relevance of this method.