On routing and performance comparison of techniques for packet-switched networks using learning automata
Athanasios V. Vasilakos, Stavros Koubias · 2003
Distributed adaptive routing algorithms with the ability to adaptively proportion traffic over several paths is proposed for packet-switched data networks. A learning automaton is situated at each node of the network where a routing decision must be made and directs traffic entering the node onto one of the outgoing links. Using network feedback, and automaton modifies its routing strategy to improve its link selections. This approach has the advantage over existing routing schemes of offering a simple and extremely practical feedback and updating policy.>