LABON: a learning automata-based optical network

A WDM optical network which makes use of learning automata in order to achieve a high throughput and a low delay under any load conditions is introduced. An array of learning automata which control the passing of the transmitted packets to the star coupler is placed at the network hub. Each wavelength is controlled by a specific automaton which contains the probability that a packet transmitted at this wavelength will pass to the star coupler. After each time slot the passing probability of each wavelength is modified according to the network feedback information. The asymptotic behavior of the system which consists of the automata and the network is analyzed and it is proved that under any load conditions, the passing probability asymptotically tends to take its optimum value. Furthermore, simulation results are presented, which indicate that significant performance improvement is achieved when the proposed learning automata based passing mechanism is used