Research: WDM passive star networks: a learning automata-based architecture

  • Authors:

  • Georgios I. Papadimitriou;Dimitris G. Maritsas

  • Affiliations:

  • Department of Computer Engineering, University of Patras, GR 26500, Patras, Greece and Computer Technology Institute, P.O. Box 1122, GR 26110, Patras, Greece;Department of Computer Engineering, University of Patras, GR 26500, Patras, Greece and Computer Technology Institute, P.O. Box 1122, GR 26110, Patras, Greece

  • Venue:
  • Computer Communications
  • Year:
  • 1996

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Abstract

A Wavelength Division Multiplexed optical network which makes use of learning automata 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 on 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, extensive simulation results are presented, which indicate that the use of the proposed learning automata-based passing mechanism leads to a significant improvement of the network's performance.